Information Unlimited Magazine – Special AUTOMOTIVE by COPA-DATA

S P EC I A L I S S U E 2020

T HE COPA-DATA M AGA ZIN E

SPECIAL AU TOMOT I V E

produc t s & serv ices

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S ERVI C E G R I D

FAQs

Everything you ever wanted to know about the zenon Service Grid Now it’s easier than ever to use the Internet of Things in industry

The zenon Service Grid is the perfect addition to the Software Platform, particularly for distributed applications. Here, we’ll consider the particular benefits of this software expansion. Why is it ideal for equipment distributed across a country or around the globe? How does it establish the connection between a company’s OT and IT networks? How is it installed and what license models are available? The answers to all these questions and more can be found here. Is the zenon Service Grid intended to replace zenon Runtime, zenon Logic, and the zenon Analyzer? No. The zenon Service Grid expands the platform in the direction of the Internet of Things (IoT). It is not a standalone product. Rather, it is an IoT upgrade for the zenon Software Platform that enables completely new applications. The zenon Service Grid was designed in line with current best practices and state-of-the-art approaches to software development. It uses architecture concepts such as microservices, bringing together several individual software components to form a large, scalable application. The distribution of the components allows you to make efficient use of the existing hardware resources. What are the key benefits compared to other IoT solutions? The zenon Service Grid allows you to monitor data from distributed locations in an integrated solution. In conjunction with the Service Grid, the zenon Software

Platform makes it possible to transfer data continuously from the fieldbus level to the cloud within a single system. The central development environment makes engineering easier and reduces the amount of work required overall. Thanks to the backward compatibility, existing projects can also be easily integrated into the overall system. How does the Service Grid help to protect the OT network? The zenon Service Grid works exclusively with unidirectional connections. All nodes use outgoing connections to communicate with the Service Hub – this includes zenon Runtime. Communication is encrypted via Transport Layer Security (TLS) and the participants’ identities are verified by means of digital certificates.

produc t s & serv ices

What kind of applications is the Service Grid best suited to? The main purpose of the zenon Service Grid is to provide a simple connection between geographically distributed zenon installations – in the case of international production sites, for example, or in the field of power generation. The collected production data can be visualized in a central location, such as a control center, with the aid of zenon Runtime or the HTML Web Engine. The Service Grid can also be used as a security gateway between OT and IT networks to transfer data from the field level to third-party systems in the IT landscape. For more information on this subject, please refer to the previous article, which contains further concrete examples. Is the Service Grid intended to replace the zenon network? No, the zenon Service Grid and the zenon network can and should exist in parallel and each should be used appropriately, as the situation demands. When does it make sense to continue using the zenon network? The zenon network is used in the context of OT within one plant to synchronize runtimes with each other. The zenon Service Grid, on the other hand, is generally used in conjunction with WAN connections over large distances to process selected data from zenon Runtime or zenon Analyzer in a cloud application or a local data center. Which systems can be integrated for the purposes of exchanging data? The zenon Service Grid is primarily used to exchange data between the software components of the zenon Software Platform: i.e. between zenon Runtime, zenon Analyzer, zenon Logic, and the HTML Web Engine. To guarantee the security of the data and the data exchange process, external systems cannot be integrated with the Service Grid’s internal communication layer. Third-party systems can obtain data for further processing via the Service Grid API’s REST interface. What kind of data can be exchanged via the Service Grid? The Service Grid supports various types of data. Process data such as variables, alarms, and events can be exchanged in large volumes. As well as distributing real-time values, the system can also access historical archived values. Furthermore, you can set whether each individual data point should be available as read-only, available for read and write access, or not available at all in the Service Grid. Alarms can be confirmed and linked with comments as well as causes. The Service Grid also has an interface

with zenon Analyzer, which can be used to generate and retrieve reports. zenon Analyzer also allows you to use all existing SQL-stored procedures to carry out data analysis. Engineering data can be synchronized between zenon Editor and zenon Analyzer, ensuring that zenon Analyzer metadata is always up to date. Is the zenon Service Grid scalable? A stable, high-performance system essential, particularly in the case of large distributed systems with numerous plants. For years, zenon Runtime has served as a stable foundation for data acquisition and analysis, as well as process control in such environments. The zenon Service Grid responds dynamically to high load peaks. A higherlevel management system records the utilization of individual services and can implement scaling measures. Through a generic approach with container-based applications, you can scale each service independently within the zenon Service Grid. You have free choice when it comes to the container platform and the management system. However, COPA-DATA recommends using Docker and Kubernetes. Instructions for operation on the basis of these platforms can be found in the help documents. Why is the REST interface provided in the zenon Service Grid? REST interfaces are widely used and are a popular way of exchanging data between software systems via HTTPS. Further benefits include the fact that they are not dependent on any particular programming languages or platforms, they are optimized for large data volumes, and they enable the connection of mobile applications. REST interfaces are not standardized and are always configured for the specific application in question. They support various data exchange formats, including JSON, XML, and any type of text format. What does the Service Grid do in the event of a network failure? zenon allows you to evacuate historical data from zenon Runtime into zenon Service Grid. If the network connection fails, the entries are buffered until communication is reestablished. Following successful synchronization, the local memory is enabled again, thus preventing data loss. How are user authorizations implemented? The authentication and authorization mechanism is based on a two-stage concept. In the first stage, the user is authenticated by means of the Identity Service, thereby answering the question “Who am I?”. The Policy Service is then used to decide what rights the user has, thus answering

produc t s & serv ices

the question “What am I allowed to do?”. This system makes it possible to implement complex access rights. Do staff need specialized IT knowledge to install and operate the zenon Service Grid? Your IT staff will need some in-depth knowledge; for example, to tailor the required parameters of the individual services to the installation platform. This is carried out directly via configuration files during installation. If you want to benefit from advanced functionalities, such as dynamic scaling and failsafe performance, you will need to use technologies such as Docker and Kubernetes. Specialized knowledge and experience are required in this case, as the IT staff will be responsible for operating and maintaining the installation in the long term, including taking care of troubleshooting and software updates. Does the Service Grid only run in a particular cloud environment? The zenon Service Grid is platform-independent and cloudindependent. You can choose any cloud provider or opt for operation within a private data center. Why are new technologies such as Docker used? It is particularly advantageous to use new technologies when running web applications in the cloud environment. Application requirements such as scalability, platform independence, and easy installation can be achieved more easily and efficiently with these technologies. Where are the installation packages and how do I install the zenon Service Grid? The process varies depending on the type of installation. A Windows setup program is available for classic installation, which should be carried out on the server hardware and server operating system. For installation in a cloud environment or a local data center, Docker images are available in the COPA-DATA registry. These images should be installed on an existing Kubernetes cluster. How are the Service Grid’s individual components updated? In the case of classic installation, the individual components are updated with the ISO installation package. If the Service Grid is operated with Kubernetes, you can easily update the components by using the latest Docker images. In both cases, only the components’ binary files are updated. The configuration of the Service Grid installation remains the same. This means that you can continue using the system immediately after the update.

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Do I need an SLA for the Service Grid? You will need a valid service level agreement (SLA) to purchase and operate the zenon Service Grid. This will give you access to the latest security updates and functional enhancements at all times. Improvements are implemented in the zenon Service Grid on an ongoing basis and are provided via the COPA-DATA registry. What license models are available? You can purchase the zenon Service Grid as a monthly subscription with billing on an annual basis. The Service Hub, Data Storage, Identity Service, and Egress Connector components are included. The Ingress Connector can also be licensed, if necessary. In this case, the price is dictated by the number of variables in the existing zenon Runtime. The connection between the Web Engine and the Service Grid can be configured either as a read-only connection or a read-and-write connection, whereby licensing is based on the number of users. Any further components connected via the API Gateway can have either a read-only or a readand-write connection. Furthermore, a connection from zenon Analyzer to the zenon Service Grid can be licensed to output reports via the Web Engine or the API Gateway. How does the release cycle for the Service Grid compare to zenon Supervisor and zenon Analyzer? We have been systematically developing and refining the zenon Software Platform over the last few years. With the next version – zenon 10 – zenon Software Platform components will be released simultaneously for the first time, including the zenon Service Grid. An annual release cycle is regarded as appropriate in the OT world, but is not fast enough for cloud scenarios. COPA-DATA will, therefore, offer the zenon Service Grid in two different versions. The version with long-term support will be released annually with the other zenon Software Platform components. To enable timely updates and enhancements, there will also be three further releases: one at the end of each quarter. You are free to choose the option that best suits your needs.

Optimizing production with a time machine How the zenon Process Recorder enhances productivity and quality

Manufacturing processes in the automotive industry are highly optimized because malfunctions, downtime, or faulty process control can have serious consequences for production. To analyze these influencing factors, data from various sources has to be interpreted and connections identified. It therefore makes sense not only to use zenon to collect data, but also to analyze it. This is where the zenon Process Recorder comes into play. Published in

information unlimited the copa-data magazine No. 35, November 2019 ÂŠ Ing. Punzenberger COPA-DATA GmbH www.copadata.com/iu

industr ies & solu tions

This zenon module uses the usual zenon process screens, but instead of simply displaying current values, you can display data from any point in time. Additional controls are used to select these points in time and the recorded values can be continuously played back, much as you would playback a recording. However, the runtime can still be navigated as it is during live operation and the user simply switches between the various screens. Thanks to this zenon “time machine,” the user can retrospectively view and analyze past process sequences at a selected point in time. Replays can be displayed as often as required and provide insights into influencing factors that are often not apparent at first glance. G O I N G TH E WRO N G WAY – A N E X A M P LE F RO M CO N V E YO R TE C H N O LO GY In this example from one COPA-DATA customer, car bodies from different series are transported via a mix point. Several controllers are used to control the conveyor technology and the PLCs exchange data through the controllers via direct interfaces. The vehicles are identified via conveyed data carriers, and the conveyor destinations are determined by sending queries to the control system. Using zenon, this system is monitored from a control room and the users can also intervene, for example, by redefining the destinations or blocking or setting transport routes for individual vehicles. In individual cases, vehicles may be transported to incorrect destinations or not delivered within the specified time period. The zenon Process Recorder is therefore used to analyze the causes. The module is integrated with the existing zenon project and records the variables from the connected controllers. The Process Recorder can be configured at the click of a mouse and, due to the optimized recording process, there is no noticeable impact on the servers’ CPU. The memory space that the data requires is also low. In addition to current data processing functions, the zenon mix point servers now also record the Process Recorder values. Since the Process Recorder playbacks can be viewed on a separate workstation provided in the control room for data analysis, the mix point can still be controlled online without being affected by the module. R E P RO D U CI N G P RO C E S S E S WITH TH E S I M U L ATI O N MODE On a control-room workstation, the zenon client can start the Process Recorder in a simulation mode. Regardless of the online connection to the server, the Process Recorder uses the recorded data to display the values on the monitors. A special control screen enables the user to navigate along the timeline. It lists the timestamps of the recorded data. Similar to a media player, it also features buttons for going forward and backward, playing, or pausing the recording. The situation in question can thus be displayed for analysis on the monitor. The user can then use the control elements to repeat certain situations at will or to stop the display to analyze the data. In this specific application, the module has already been used successfully to determine the cause of incorrect vehicle deliveries. As a result, the overall control system has been further optimized. I M P ROVI N G Q UA LIT Y WITH A N E X A M P LE F RO M CO M P O N E NT P RO D U C TI O N In another case, the Process Recorder is used in component production where the workpieces are processed by machines from different manufacturers. Moreover, environmental influences such as the ambient temperature have to be controlled, as they influence production quality. A machine data acquisition system (MDA) based on zenon is used for production control, while the zenon

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S I M P LE P ROJ E C T CO N F I G U R ATI O N O F TH E P RO CE S S R E CO R D E R I N FO U R S TE P S –

Ac tivation of th e Process Re cord e r in th e proje c t

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Creation of th e scre e n a n d th e f un c tion for th e control of th e Process Re cord e r in simulation m ode

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Playba ck of past eve nt s in proje c t simulation mo d e , in th e process scre e n dire c tly

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Server Process Recorder activated: The server records process data

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Process T he P r oce s s Re cor de r cont i nuou sly r e cor d s pr oce s s e s , wh ic h c a n late r b e playe d bac k i n det a i l on t he pr oce s s s c r e e n i n a s i m i la r w ay to a me d ia playe r. O n ly t he r e leva nt t i me f ra me w i l l b e t ra n s fe r r e d to t he ze non c l ie nt ; t he r e s t of t he d at a i s h idde n.

direct drivers are used to read and process the production and quality data from the individual machines in a central location. In addition, the system connects energy meters and data from the air conditioning systems. The determined values enable the calculation of production figures, energy consumption, quality indicators, and production reports. In this case, the Process Recorder was set up to further optimize production. The Process Recorder data was subsequently analyzed on the MDA screens, enabling users to determine previously unknown correlations between different influencing factors. The investment in the Process Recorder quickly paid for itself through an increase in production quality and the prevention of rejects. S I M P LE CO N F I G U R ATI O N The Process Recorder can be integrated with existing zenon projects quickly and easily. As an integrated module, it only needs to be activated with a user license. The individual projects are then configured at the click of a mouse, simply by enabling the variables to be monitored. It is not necessary to set save cycles, as the Process Recorder records data based on events. Only two functions are required to start and end simulation mode. A separate screen type is available for controlling playback in simulation mode. The existing zenon screens are used for display and analysis purposes and do not need to be adapted. As a result, the Process Recorder helps users gain an in-depth understanding of the interaction between the

machines and equipment used. By displaying the data and operating actions from various subsystems or controllers, it is a valuable addition to effective production optimization.

BERND WIMMER Industry Manager Automotive Bernd Wimmer has been Industry Manager Automotive at COPADATA Germany since 2002. Previously, he worked as a specialist for central control technology for TaurusMediaTechnik GmbH. He lives with his wife, two children, and their cat in beautiful Bavaria.

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NEW TECHNOLOGIES SET TO IMPROVE FUTURE MOBILIT Y Never-ending traffic jams, fine-dust pollution, and insufficient parking spaces – private transport in our cities has just about reached its limits. City and traffic planners and the automotive industry need to find new strategies in order to improve urban mobility. The vehicle manufacturing sector itself is also experiencing radical change, with innovative technologies leading to increased process efficiency. Today, carmakers are facing a battle on multiple fronts in order to keep up with the competition.

Over half of the global population currently lives in cities. By 2050, this figure is set to rise to 70%. And in almost every city, the number of cars is growing at a faster rate than the number of inhabitants. While, on the one hand, this may well signal a positive development for motorists, fine-dust pollution and never-ending traffic jams are leading to a serious rethink for many. By 2050, experts warn, the amount of urban traffic in circulation could have trebled. New mobility concepts are therefore urgently required in order to meet these challenges. S M A R T TE C H N O LO G I E S A N D C A R SHARING Smart technologies could offer a promising solution. These technologies offer the possibility of networking mobility functions such as traffic planning and public transportation and optimizing them based on usage data gathered by sensors. Intelligent traffic control systems capable of operating in real time could facilitate safe, proactive travel, reduce the risk of congestion along certain stretches, and ensure that traffic routes and parking spaces are used as efficiently as possible. Even smarter would be systems which feed all traffic data into a personal program, which then uses algorithms to learn the user’s travel habits and recommends the best routes and modes of transport, or points out free parking spaces. However, there are a few obstacles to overcome before ideas like this can start to take real shape. In particular, concerns over data protection and the lack of unified standards are currently putting the brakes on further developments in this area. Published in

information unlimited the copa-data magazine No. 34, June 2019 © Ing. Punzenberger COPA-DATA GmbH www.copadata.com/iu

What’s more, solutions like this won’t actually be enough if traffic continues to expand at the rate that it’s going. Functioning alternatives to private cars must be developed to bring city dwellers quickly and flexibly from A to B. This presents completely new challenges – not only for the cities themselves, but also for car manufacturers. Young people are becoming less and less enthused by the concept of the car. In cities, in particular, owning a car is increasingly seen as unnecessary, while car sharing and ride hailing – that is, the opportunity to share rides in the city – are enjoying rising popularity. BMW and Daimler brought their own sharing-economy offerings to the market several years ago in the form of DriveNow and Car2Go respectively. Now, these companies have announced that they will be merging their car-sharing fleets and closely interlinking their mobility services in the areas of ride hailing, parking, charging, and multi-modality services. AU TO N O M O U S D R IVI N G A N D A LTE R N ATIV E F U E L S Some of the greatest hopes for the mobility of tomorrow are pinned on the concept of autonomous driving. In Singapore, self-driving test cars have been on the roads since 2016. Driverless buses, lorries, and robot taxis are set to take to the streets in regular operation by 2022. In this part of the world, car manufacturers are turning their attention to selfdriving robot taxis which use existing transport networks and therefore don’t require new infrastructure. For this breakthrough to succeed, however, a few roadblocks still need to be navigated. A car without a driver throws up a

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TH E U S E O F AU G M E NTE D R E A LIT Y I N V E H I C LE M A N U FAC T U R I N G H A S A N U M B E R O F TA N G I B LE A DVA NTAG E S :

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F E W E R M I S TA K E S : Th e ste p - by-ste p display of data a n d instruc tions re d uces pro d uc tio n e rro rs . Employe es kn ow exa c tly which pro duc tion ste p com es n ex t .

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SMOOTH PROCESSES: N ot only do es th e A R syste m provid e info rmatio n on th e pre cise ord e r of process ste ps , it c a n also display th e exa c t position of pa r t s

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T I M E S AV I N G : Releva nt information is displaye d a utomatic ally, mea ning e mploye es n o long e r have to sea rch for th e right docume ntation .

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Q U A L I T Y: Regula r sc a ns a n d ch e cks re duce th e e rror rate a n d minimize reje c t s .

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SHORT DEVELOPMENT TIMES: M a n ufa c ture rs n o long e r have to sp e n d signif ic a nt a mo unt s of time painsta kingly ma king protot yp es by ha n d . I nstea d , th ey c a n simply proje c t protot yp es onto a n availa ble sur fa ce in a mat te r of se con ds , saving both time a n d mate rial cost s . Th e proje c te d protot yp e also of fe rs a d etaile d view which c a n b e broke n down into in dividual pa r t s .

whole host of legal and moral questions; not least who is liable in the event of an accident and in connection with the life-and-death decisions that must be made in situations where such decisions are unavoidable. Finally, algorithms for self-driving cars only work when they have been properly trained using video recordings from actual traffic situations – something which, however, goes against current data protection regulations. Alternative fuels are also set to play a significant role in the mobility transformation. While electric cars cannot solve the ever-growing traffic problem, they can help to improve air quality and reduce noise pollution in cities. Admittedly, we might have a while to wait yet before any real breakthroughs are made. However, as far as the EU’s climate change goals are concerned, in the long term, the classic combustion engine is set to become obsolete. This is something no car manufacturer can afford to ignore if they wish to remain competitive in the international market. N E W TE C H N O LO G I E S FO R E F F I CI E NT V E H I C LE M A N U FAC T U R I N G At the same time, the car manufacturing industry must also be prepared to overcome challenges in another area: production. Against the backdrop of Industry 4.0, more and more processes are being automated and restructured. These developments open up entirely new possibilities for the automotive sector. One example of this is augmented reality (AR) – that is, the overlaying of reallife scenarios with virtual information as part of the construction and planning of new models. Manufacturers like Volkswagen are already producing 3D models which are being used to plan the entire car body. Changes and corrections can be made on the projections instantaneously, and special models or customer requests can be implemented more quickly during assembly. This is where automation software like zenon comes into play. Not only does this software take care of both energy data management and automated engineering, it also enables users to create “digital twins” in order to define significant performance features before going into production.

With the shifts in mobility in our cities and the rise of new automation technologies in the vehicle manufacturing process, the automotive industry is facing a battle on two fronts. New competition, in Asia in particular, is giving established manufacturers a run for their money. In part, progress is being driven by legal requirements. In China, for example, electric cars must make up a minimum of 10% of cars sold by any given company from 2019. In France and the UK, combustion engines are set to be completely banned from 2040. Other governments will doubtless follow suit. And Tesla boss Elon Musk wants to completely revolutionize the way we travel. Against this backdrop, car manufacturers have no time to lose.

ber nd w immer , industry m a nager au tomoti v e

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ZE NON SUCCE SS STORY TH E A DAC C H O OS E S CO PA- DATA FO R ITS B U I LD I N G M A N AG EM ENT VI S UA LIZ ATI O N

Flexible and absolutely fail-safe – building automation with zenon

The ADAC (General German Automobile Club) wanted to introduce end-to-end centralized building services management at its new headquarters in Munich. The old and rigid system was to be replaced with a flexible modern solution that would be able to meet the varying needs of the approximately 2,500 employees working in the new building. The ADAC was able to achieve this with zenon software from COPA-DATA, which is used to monitor and visualize every single element of the building’s technology. Published in

information unlimited the copa-data magazine No. 34, June 2019 © Ing. Punzenberger COPA-DATA GmbH www.copadata.com/iu

industr ies & solu tions

With 20 million members, the ADAC is Europe’s largest automobile association. It is renowned for its breakdown recovery and accident rescue services. Its yellow angels are called upon for help about 10,000 times every day. Approximately 2,500 employees work at its headquarters in Munich. With its colorful and modern facade, the new building has been a striking feature on Munich’s skyline since its completion in 2011. One of the goals in the construction of the new building was to introduce a centralized control system that controls ventilation, heating, lighting, and power supply. “The existing technology gave us very little scope to adapt to new requirements and make changes. We wanted to move away from this,” explains Markus Lamers from the building services team. G R E ATE R F LE XI B I LIT Y TH A N K S TO M O D E R N B U I LD I N G CO NTRO L SYS TE M The ADAC’s headquarters houses various departments under a single roof. “We’re home to 100 professions,” says Markus Lamers. There’s a print shop, training rooms, goods-receiving department, TV studio, canteen, and conventional office spaces – all of which have very different room temperature, lighting, and ventilation requirements. Frequent location changes for employees or entire departments also have to be accommodated. It has to be possible to adapt the interior spaces specifically to meet the needs of their inhabitants.

the sun, and temperatures, forwarding its findings to the solar protection system controllers. Around the building, more than 1,000 distributed PLCs control these data points. VI S UA LI Z ATI O N , CO NTRO L , A N D O P TI M I Z ATI O N O F CO M P LE X EQ U I P M E NT Given the high number of data points, planning interfaces and connectivity was a very important consideration when selecting suitable software. The decision-makers at ADAC wanted to introduce an open system that would support a flexible choice of hardware and control systems. Good visualization of fault management so problems can be located and dealt with quickly was another important factor, in order to make work easier for engineers. S TRO N G PA R TN E R S WO R K I N G TO AC H I E V E A CO M M O N G OA L Collaboration with COPA-DATA got underway even when the building was still at the planning stage. A demo version of zenon was tested. The SCADA software impressed with its platform independence, wide and varied interfaces, and customizable display options for visualization. All of the components in the building control system are managed in an equipment identifier system (EIS). A main overview and an alarm message list provide information about possible faults and their status. If limit values of variables

“zenon software provides us with a window into the technology. It makes our work so much easier.” MARKUS LAMERS, ADAC BUILDING SERVICES MANAGEMENT TEAM

So that it would be best placed to respond and adapt to the wide and varied requirements inside the building, the ADAC prioritized maximum flexibility when constructing the new building. The entire building technology, with more than 55,000 hardware variables, can be controlled remotely, enabling it to be adapted at any time. Each individual light, for example, is represented by a variable. The individual hardware variables generate a total of more than 400,000 virtual variables, which are used for monitoring and control of the entire building services. For example, all of the shutters are controlled from within the system. A central weather station analyzes luminance levels, the position of

are breached, an alarm or a fault message is triggered. Individual application screens visualize every aspect of the building technology. Should a fault occur, it is easy to track where it is located. Lamers says, “This provides us with a window into the technology. The engineers can see immediately exactly where the problem is. This represents a huge time-saving for us.” F LE XI B LE ACC E S S FO R O P E R ATO R S zenon can be accessed via the zenon Web Client from more than 25 operator stations at centralized locations inside the building. Equipment plans and the alarm message list are

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Figure 2: Vi s u a l i z at ion of t he cool i n g d i s t r ibut ion net work . A ny pa r t of t he bu i ld i n g c a n b e s e le c te d d i r e c t ly i n t he v i s u a l i z at ion.

Figure 1: St at u s of a l l a r ea s at a g la nce. Fau lt s a nd me s s a ge s a r e color-co de d.

thus easily available in all significant locations. Members of the building services management team can even access the system from home. This safeguards the availability of the highly sensitive areas that are relied upon 24/7 (accident rescue or casualty evacuation, for example), including outside normal working hours. R E D U N DA N C Y FO R G R E ATE R R E LIA B I LIT Y At the ADAC, zenon runs on two independent servers. This redundancy maximizes the reliability of the system. One server is always in regular operation, while the second runs in standby, serving as a backup. Should the first server fail, the second will automatically take over all functions without any loss of data. E XPA N S I O N TO I N C LU D E M O R E B U I LD I N G S The ADAC is currently planning to integrate more buildings into the central control application. Until now, these buildings have been controlled by a separate system. “zenon’s open design gives us the flexibility to expand the central control system and achieve a uniform standard for our building automation,” explains Lamers. The advantage: The building services management team has to master only one system to be able to operate equipment across all sites.

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Flexible , ex te nsive B M S that a da pt s to cha nging re quire me nt s

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5 5 ,0 0 0 va ria bles provid e compre h e nsive b uilding se r vices ma nag e me nt

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Plat form -agn ostic solution that easily integrates with h ete rog e n e o us syste ms a n d ha rdwa re

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Customiza ble ala rm messaging

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O ppor tunit y to integrate multiple sites into a single syste m

CO NTAC T: An d rea s Zerlet t S ales E xcelle n ce En e rgy & I nf rastruc ture / S ma r t Cit y CO PA- DATA G e rma ny a n dreas . ze rlet t@ copa data .d e

EFFI C I EN C Y TH RO U G H ERG O N O M I C D E S I G N O F P RO D U C TI O N P RO C E S S E S

THE CHANGING FACE OF AUTOMOTIVE PRODUCTION “Any customer can have a car painted any color that he wants so long as it is black,” Henry Ford is famously quoted as saying in the early era of automotive mass production. It’s a thought that still raises a smile, but the fact is that today’s buyers demand a wide range of models to choose from as well as customization options. This has consequences for the way in which production lines are organized and the software solutions required to facilitate them. Powerful visualization systems help staff to maintain a view of the bigger picture in production and logistics applications. Published in

information unlimited the copa-data magazine No. 33, November 2018 © Ing. Punzenberger COPA-DATA GmbH www.copadata.com/iu

industr ies & solu tions

As product portfolios grow, conventional manufacturing processes – and limited production space – are no longer able to accommodate them. Automotive manufacturers therefore rely on flexible production and capacity management in order to manage model diversity and guarantee the customer individualized production. The industry also faces the challenge of minimizing tied-up capital by dispensing with interim storage as much as possible.

S IA M E S E T WI N S : LE A N P RO D U C TI O N A N D TR A N S PA R E NT S U P P LY C H AI N S In 2013, a case study by the Fraunhofer Institute on the topic of Industry 4.0 and smart factories predicted an increasingly intensive shift toward lean production in automotive manufacturing. This has certainly come to pass: today, automotive manufacturers around the world make cars according to lean production principles. A lean, flexible approach is the only way for these companies to maintain their competitiveness. The goal of lean production is to eliminate all areas of waste from production processes while also increasing efficiency and effectiveness in manufacturing. In basic terms, the lean production principle calls for production to be strongly aligned with customer demand. The aim is to only produce what customers require and to do so at the point in time when they need the product. To boost production efficiency, stocks of material are reduced to the absolute minimum and interim storage is restricted as much as possible. Meanwhile, resources must enable the shortest possible throughput times in order to increase production effectiveness. With this kind of production, the manufacturer is able to respond to customer requirements quickly and flexibly and, at the same time, maintain a high number of variant models in low batch sizes. In this context, lean production is based on the “just in time” (JIT) manufacturing principle. Primarily, the system relies on a transparent supply chain: purchasing, logistics, and manufacturing must be tightly meshed together so that the required raw materials are provided to the production stage at the right time.

J U S T- I N -TI M E : D E M A N D - BA S E D A S S E M B LY A N D M A N U FAC T U R I N G According to the JIT principle, the product is produced in line with customer requirements without time, materials, or staff resources being wasted. The idea is that this

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reduces inventories and capital tied up in inventory and means that materials and products no longer have to be produced in advance in large volumes, but instead assembly and manufacturing are conducted on demand in a flexible manner. This shortens lead times, saves on warehouse space, and reduces storage costs in the medium term. In order to keep producing goods reliably, cheaply, and quickly just in time, centrally managed optimization is dropped in favor of distributed coordination. P RO D U C T S WITH LOT S O F VA R IA NT M O D E L S R EQ U I R E A S H I F T I N P RO D U C TI O N A P P ROAC H The challenges facing automotive manufacturers today are short production cycles, maximum diversity of variants, outstanding productivity, and flexible utilization. However, as the variety of models available keeps growing rapidly, the strengths of the JIT production method can no longer be harnessed to its full potential. Maintaining the principle of JIT production would require even more complex manufacturing systems. In addition, the very high levels of product variance make a separate interim storage space and part store necessary for each model in the production line, taking up immense volumes of production space in conflict with the JIT principles of minimizing stock, space, and resources. It would fly in the face of the advantages and strengths that the JIT concept has to offer. To solve this dilemma, manufacturers have enhanced the JIT concept further, developing the just-in-sequence (JIS) principle – also known as the “pearl chain” process.

J U S T- I N -S EQ U E N C E : A FO CU S O N P RO D U C TI O N -SY N CH RO N IZ E D AVAI L A B I LIT Y O F A LL PA R T S Faced with such a variety of models and variants, body construction is moving away from single-type production and into sequential production instead. As a productionsynchronized procedure, JIS represents a refined just-intime concept. In body construction, it is common for a production plant (sink) to require resources from several other production lines (sources). As a result, the sources must coordinate their sequential production arrangements among themselves so that the sink is given the right components at the right time, in line with the first-in-first-out (FIFO) principle of manufacturing. Members of staff in production also benefit from the advantages of the JIS principle: all the parts needed for each work step are provided in the correct order, and there are no areas that are prone to error.

industr ies & solu tions

ust-in-ime (jit)

ust-in-sequence (jis) Order placed

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CO M M U N I C ATI O N A S A S U CC E S S FAC TO R Above all else, there must be good communication between the various partners in the supply chain, and the information provided must be valid and easily accessible. If this is not the case, this could result in an unstable material flow that prevents successful manufacturing and, in a worst-case scenario, leads to production being halted. To avoid this, as a check of last resort, the human factor can be incorporated into the automated system. Ultimately, experts in production and production logistics must decentralize decision-making power. For this purpose, they require the right information being provided at the right time. So what’s the best way of explaining the complexity of this process to users? And how do we make it easier for them to follow? These questions have been around

since the birth of the first computer and are an integral part of human-machine communication, as well as other interdisciplinary sciences. As machines and their day-today use have modernized, these are questions that have given rise to a new scientific discipline: ergonomics.

E RG O N O M I C DATA P RO C E S S I N G From an ergonomic point of view, it is important to provide a user-oriented communication interface for processing data and displaying information. The data should be filtered and processed by the production system, meaning that the user receives only essential and relevant information. The advantages of this are that no unnecessary information can sway the decisions that a user makes and the user is given a better overview of the process. The filtered information must be displayed

industr ies & solu tions

in a way that allows the user to interpret and analyze information effortlessly and unambiguously. With this goal in mind, visualizations provide a much faster overview of complex matters than text-based descriptions permit.

Z E N O N P ROVI D E S A N OV E RVI E W O F P RO D U C TI O N Another key consideration in the sequential production process is the availability of data and information. These must be accessible at all times – and everywhere – so that users can respond more quickly to unexpected events, for example, during production. In particular, web technologies and mobile devices, such as smartphones or tablets, allow flexible access to communication with machines and provide new possibilities of handling data, thus making it easier for users to grasp complex issues. A further opportunity presented by Industry 4.0 is the networking of buildings, control systems, and sensors with production systems to create an IoT world that incorporates data and services. This allows the availability of realtime information relating to production processes to reach unparalleled levels of quality. As a result, data modeling is increasingly able to reflect the current state of affairs and production processes become more transparent as a whole. zenon is a system that enables ergonomic and modern visualization, abstract data processing and constant transfer, uninterrupted availability of data, and accessibility across a variety of devices. CO N C LU S I O N In the past, the ergonomic aspects of visualization and the processing of data received very little attention. In industrial production, graphical interfaces were usually designed quickly and without much consideration since the complexity of the processes was relatively limited and the focus was firmly on the ability of the system to run. In the future, however, a focus on ergonomics will be unavoidable due to the changing nature and increasing complexity of production environments. An increasing focus on customers and their demands for individuality in products will be essential to maintain competitiveness. And, as things stand, this means that there will be no end in sight to the increasing complexity of production environments. The subsequent necessary consideration of ergonomics marks a further step toward Industry 4.0.

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I NTERVI E W WITH F U T U R I S T L A R S TH O M SO N

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How Artificial Intelligence, Disruptive Innovations, and Changes to our Mobility are Changing the Automotive Industry

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Autonomous driving, electric vehicles, and car sharing – the automotive industry is currently facing probably the biggest changes it has experienced in its entire history. At the same time, digitalization is revolutionizing production at a breathtaking rate. For the first time, this period of change is seeing new players enter the market and put pressure on the major manufacturers with disruptive ideas and a high degree of innovation. How can automotive companies navigate the path to Industry 4.0? How can they stay competitive? And what will the mobility of tomorrow look like? We spoke to futurist Lars Thomson about Production 4.0, artificial intelligence, and the mega-trends in the automotive industry.

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No. 32, October 2017 © Ing. Punzenberger COPA-DATA GmbH www.copadata.com/iu

O U R I NTE RVI E W PA R TN E R :

LARS THOMSON His theses and future scenarios are as accurate as they are provocative. Lars Thomsen is one of the world's leading futurologists and is one of the most influential experts on the future of energy, mobility, and smart networks. For over 20 years, he has been a self-employed consultant working with companies, corporations, institutions, and governmental agencies in Europe on the development of future strategies and business models of the future. He is the founder and chief futurist of the future matters think tank. Over the years, more than 800 companies have placed their trust in his expertise and nose for a trend. He uses roadmaps to predict a trend over a period of 520 weeks. His research focuses on the calculation of tipping points – disruptive developments in technologies, markets, and business models – each with a strong economic impact on industries and players. With his tried-and-tested methods, he succeeds in determining these points with an accuracy of around 18 months. Lars Thomsen is a keynote speaker at national and international congresses and meetings, giving lectures that inspire a wide range of audiences.

industr ies & solu tions

Digitalization has greatly transformed the manufacturing industry in recent years. What have been the biggest changes? There are multiple phases to digitalization. In the first stage, we abolished all analog processes. Now it is about connecting all the elements involved in a process to the digital world. When we talk of digitalization as an emerging megatrend, however, it is somewhat misleading in my opinion. After all, we have been digitalizing our communication, our way of working, and much more over the last 30 years or so. From my futurist's perspective, I would say that the real change in manufacturing has only just begun. Namely, through artificial intelligence and the next developmental stage of the Internet (the Internet of Things) we will introduce completely new and unique intelligence into production. What benefits can this bring to manufacturing? Over recent years, a digital nervous system has emerged that has made machines and entire production facilities intelligent. Systems use pattern recognition to learn to avert mistakes and improve processes. I like to call this development “the end of stupidity”. Before, we had to make do with machines that were so “stupid” that people were always required to set them up and repair them. Thanks to artificial intelligence, machines and entire production systems can suddenly think for themselves. According to the Digital 2016 Monitoring Report from the German Federal Ministry of Economics and Technology, we are only seeing an “average level of digitalization in companies” in the automotive industry. Why do you think that is so? Because, to remain competitive, digitization was simply not necessary for a long time. The automotive industry has hitherto been a very protected industry. The goal of automotive manufacturers was to produce their next models more economically, more efficiently, and faster. But they were not challenged by any other industry. And there’s another reason: a car was quite autonomous. Except for the fact it sometimes needed gas in the tank, it worked by itself. And this has changed? Yes, both things have changed. All of a sudden, newcomers from the consumer electronics and IT sectors have arrived on the scene, and are competing with the industry. These companies have a much higher rate of innovation and a different risk culture. Now, for the first time, the automobile industry is really being challenged – not from within, but from the outside. And due to digitalization, cars are no longer as autonomous. In the future, the car will be part of a networked system like a city, an energy system, or a communications structure. This increases the pressure to innovate and requires a digitalization strategy. Which innovations do automotive companies need to stay competitive? There are two different types of innovation – incremental and disruptive. While incremental innovation improves an existing system – for example, a model of car that is slightly lighter, faster, and more economical – disruptive innovations are much more fundamental. Does a car have to have a combustion engine? Or can a car drive itself? Until now, cars have had very long innovation cycles of 7 to 8 years. What is more, it is mainly about small-scale, incremental innovations. The new competitors from IT and consumer electronics have shorter innovation

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cycles and more willingness – or expectation – to innovate. Thus, the automotive industry needs agile strategies urgently, and a readiness for disruptive innovations. Why do you think the automotive industry is finding it so hard? It is all about the management and innovation culture. If there is no competitive pressure from outside and the environment is known very precisely, there is not the positive kind of paranoia perhaps needed to operate in highly aggressive markets. At the same time, the automotive industry is faced with the enormous challenge of currently being confronted by three simultaneous mega-trends: 1. What will be under the hood tomorrow? i.e. combustion engines versus electrical motors. 2. Will we have to drive our own cars in future or will our cars drive themselves? 3. Does mobility for the individual in the future mean ownership of a vehicle or just access to one? And when we realize that these three mega-trends will completely change the industry over the next decade, we will see the enormous pressure under which every decision in the production and development of automobiles will have to be made in the future. What does this mean for manufacturing in real terms? In manufacturing, we have to think “outside the box”. How can we use more flexible machines to produce vehicles? How can we increase value-add in production simply? And how can we implement changes or improvements in the production process in an agile way? For this, automobile production has a lot to learn from other industries. Experts from other industries are certainly needed to introduce new agility and a new innovative culture to the automotive sector. Tesla does this: only a minority of its developers previously worked in the automotive industry. What role does IT play? With modern IT, unique intelligence is created within production systems. Previously, the production manager needed a great deal of experience and built up valuable knowledge over years. Thanks to artificial intelligence, we are now dealing with systems that are so smart that they are not necessarily dependent on this knowledge. Intelligent systems themselves make suggestions on how processes need to be converted to complete production faster. Or they

45 19

even know themselves when a service is due – the keystone for Production 4.0. How will IT continue to change production processes in the automotive industry? Ideally, the process – from initial design through to the vehicle rolling out the factory – is supported to a far greater extent by intelligent systems and leading-edge software. This means a designer who is designing a new car on the screen is already being supported in the background by design software and production tools. In the end, the touch of a button is all it takes to produce the car in a fully automated way. At the moment, this sounds like a science fiction story but it is where we are headed! What sort of a time frame are we talking about here? The speed at which the changes are coming is rapid – much faster than most people think. Artificial intelligence, Big Data, and pattern recognition are developing much faster than the Internet. If we consider how fast development of the Internet was, and then if we raise that to the power of three, we can get some idea of the rapid pace at which changes are taking place in the development of artificial intelligence. How will Production 4.0 affect the world of work in the automotive industry? Workers who undertake very routine tasks will be replaced by robots or artificial intelligence over the coming years. This applies not only to production, but also to administration and engineering. Clearly, there will still be a need for people. However, the new requirements will create a different generation of production specialists and call for new qualifications. Those who do not deal with artificial intelligence today run the risk of not being needed in the future. This is not such a great outlook for employees. Well, there is no way to sugarcoat it. The actual turning point will probably become clear in the next two to three years – when the first manufacturers that previously produced tablets or smartphones suddenly start making cars. Today, tablets are manufactured completely autonomously. Companies will also design the product “car” from the beginning in such a way that the level of automation is similarly high to that of the production of consumer electronics.

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You mentioned three mega-trends in the automotive industry. Will these developments happen in parallel or is there a trend that will become dominant more quickly than the others? All three trends are occurring in parallel. This is what is so fascinating but also risky about the future. The price of batteries is dropping faster than all projections; by 50 percent every three years. This will lead to a parity point after which an electric vehicle is cheaper than a vehicle with a combustion engine â&#x20AC;&#x201C; in 4 to 5 years time. In the case of autonomous driving, we are looking at a similar period of time until self-driving vehicles only account for onetenth of accidents compared to cars driven by people. And then we will ask ourselves the question: as a society, do we really want to have 10 times as many accidents and traffic fatalities? And what about ownership? This is also changing in parallel with the other trends. A comparison: previously, we had to buy an expensive encyclopedia to gain access to knowledge. Today, we access the knowledge of the world through the Internet, which is much more up to date. The issue of mobility will be similar. Why should we buy a car for a lot of money if a vehicle comes to us at the press of a button, and we do not even have to search for a parking space because the car simply keeps driving? You discussed new competitors from other industries. How intensive is the pressure they are bringing to bear? One comforting fact is that building such complex devices as cars will continue to be an art form. However, I believe that over the next five years we will see around 10 new competitors enter the market, some of which will come from IT and consumer electronics. There is a lot of innovation in the new competitive situation. Take Tesla for example: the complexity of the car decreases as the drive unit is electrified. Tesla plans to reduce the number of installed parts to such an extent that the speed at which a car is produced is increased by a factor of 10 â&#x20AC;&#x201C; meaning 1000% faster than before. With conventional, incremental thought processes, this is not possible. It can only be achieved with disruptive innovations, using artificial intelligence, and the next stage of intelligent robotics. The fact that aggressive players in the market with agile software and artificial intelligence will shape the production of the future is a major challenge for the industry.

Will high-profile manufacturers survive this challenge? Whether all established brands can survive in this fight remains to be seen. Nokia was once the market leader of mobile phones, until the smartphone came and brought new players to the market. Development never fails to be exciting. And just because some trends did not come as fast as some thought, it does not mean that we will not have any changes in the coming years. This would be one of the most dangerous predictions for the automotive industry.

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industr ies & solu tions

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21 47

Digitization in the Smart Automotive Factory To satisfy the requirements of the Smart Factory, automobile manufacturing must be able to exchange data easily between different divisions and at all levels. Open engineering tools provide a flexible, scalable solution that integrates seamlessly with system enhancements. Bernd Wimmer, Automotive Industry Manager at COPA-DATA, describes how zenon can support the smart automotive factory.

F DATA I M P ROV EFor S many years, automobile manufacturing has been a WLE D G E driving force behind innovation in production technology. existing plants, more detailed Because there are so many options available to consumers, ufacturing processthe must be industry is getting closer and closer to producing ory, data is brought togetherof one”. However, continuous improvement in “batches viously organized by separate processes creates new system requirements production for everything from communications between different ment is a facility manufacturing for open, components to safety standards and highly with other systemsergonomic – one of user interfaces. Using the same systems and any cases, as well asdata standard across all disciplines is the key to “smart” automobile A, protocols specific to the manufacturing.

S E A M LE S S F LOW O F DATA I M P ROV E S P RO D U C TI O N K N OWLE D G E To increase the “value add” of existing plants, more detailed information about the manufacturing process must be gathered. In the Smart Factory, data is brought together from systems that were previously organized by separate units. A key system requirement is a facility for open, independent communication with other systems – one of the strengths of zenon. In many cases, as well as standard protocols such as OPC UA, protocols specific to the

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industr ies & solu tions

Dashboards

azure / cloud

Webclients

Security Authentication HTML5 Smart Checklist

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manufacturer also have to be supported – for example, for connecting existing equipment. Networking the different production units creates a digital model of the information, which enables the user to monitor production closely. Once process data has been gathered, the system must manage it consistently over the whole data flow – “from the sensor up to the cloud”. zenon will process, transmit, store, and display the data without any misrepresentation. Consistent data flow allows information to be used where it is needed and where it can improve production flexibility. E F F I CI E NT E N G I N E E R I N G WITH TH E Z E N O N TO O LB OX To retrieve information from data, the user needs a powerful tool with a good engineering interface. With zenon, even complex engineering tasks are quick and easy to carry out.

In routine use, zenon helps with standardization of objects and project components. The graphical zenon development environment supplies a comprehensive portfolio of options for working on the project. The “setting parameters instead of programming” philosophy, which has been a consistent feature of zenon, supports the user in carrying out tasks. Even fairly inexperienced staff can confidently make additions and amendments quickly and without error. Libraries and templates provide a large selection of use cases that can be adapted and extended for the task at hand. Another strength of zenon is its option to create distributed systems with different stations, each with specific tasks, which helps project engineers generate cascaded project structures. zenon projects can be developed, as required, by central editors or distributed

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stations. The associated databases hold the project data and are connected to a change management system.

The user can also change reports and display them with individual filter settings to make specific analyses.

F LOW O F I N FO R M ATI O N : TH E C R U CIA L FAC TO R FO R S U CC E S S Smart Factories are rarely built from scratch â&#x20AC;&#x201C; they are developed from existing production structures. This means it must be easy to embed any system in the existing infrastructure. Scalable systems like zenon provide valuable support. zenon adds the new functions to individual areas of the plant or sections of production, as well as networking them with one another. Existing hardware is reused. zenon has integrated redundancy to increase availability across the whole system. Data copied from the subsystems is processed by overlaid routines to enable machine learning, predictive analytics, and big data. zenon's communication strengths enable information to be transmitted from the sensor up to the cloud. Using a variety of target systems enhances flexibility for the user. Processing the same data for big screens as for mobile clients ensures consistency in distributed data. In addition, zenon facilitates tamper-proof data exchange between authorized users.

S M A R T AU TO M OTIV E FAC TO RY WITH ZENON The requirements of a Smart Factory are fully satisfied with zenon: its communications features complement the use of resources across disciplines perfectly. Using zenon as an ergonomic engineering tool, engineers can generate displays, reports, and user interfaces with optimum usability. Seamless integration into the existing infrastructure allows safe, efficient data processing and distribution in smart production.

TR A N S PA R E N C Y FO R B E T TE R D E CI S I O N MAKING The zenon multi-project structure with multi-servers allows distributed systems to be created. The tasks for the Smart Factory system are distributed over different machines. The â&#x20AC;&#x153;data serversâ&#x20AC;? within the zenon network carry out their specific information processing tasks autonomously. Clustering the data on the separate machines also increases processing speed. At the same time, the preprocessed data is transmitted to central databases, increasing transparency for the user and improving decision-making. U SA B I LIT Y R E D U C E S LI F E C YC LE COS T S Ergonomics and usability have an important role, especially in systems that supply the user with lots of information. A modern, task-based interface shows the user the right information at the right time, while integrated assistance systems minimize the risk of error. When working with alarms, embedded documents such as instruction manuals or links to wiring diagrams optimize the search for the cause of the alarm. Production information is presented in standardized overview windows, giving management a good basis for decision-making. Integrated reports from the zenon Analyzer also provide information on the data recorded. The system automatically generates predefined reports and distributes them by email or publishes them on the intranet.

ber nd w immer , industry m a nager au tomoti v e

S O U R C E : AU D I AG

LLY:

G EN ER ATE P ROJ EC TS I N ZEN O N AU TO M ATI C A LLY:

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zag – the Wizard for the Automotive Industry

g a wizard for ation projects. s great value on our “zag”.

With the zenon automotive generator (zag), COPA-DATA is offering a wizard for automated analysis of PLC data and the implementation of visualization projects. A major gain for the automotive industry, which traditionally places great value on standardized components and reuse. AUDI AG also relies on our “zag”.

level and a maintenance team The automation of engineering processes offers considerable eration. savings in time and costs when implementing a project. Tight ort sections are deadlines controlledcan thus be adhered to more easily. The engineer he control parameters of the simple and repeated tasks to the wizard – so can delegate tored and managed theremains for demanding activities and the risk of moreintime wever, manual intervention incorrectinproject configuration is kept to a minimum. tions from a central point is that can be examined “Zdirectly AG ” I N P R AC TI C E : AU D I AG A S A N The reason for this isEprimarily X A M P LE eamlined WindowsInCE-based automotive production, vehicle components and manual operation only requires are transported over long routes. At AUDI AG bodyshells the control room. corresponding conveyor belt systems are installed one level

above the actual production level and a maintenance team ensures interruption-free operation. The individual transport sections are controlled by central STEP 7 PLCs. The control parameters of the transport routes are monitored and managed in the attendant control room. However, manual intervention in the individual transport sections from a central point is not permitted. Only sections that can be examined directly can be controlled manually. The reason for this is primarily the safety of employees. Streamlined Windows CE-based devices can be used because manual operation only requires part of the information from the control room.

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industr ies & solu tions

S TA N DA R D I Z E D A S S I G N M E NT O F TH E B LO C K S Corresponding programs have been set up in the PLC for the control of the manual areas that belong to the panels. In doing so, each operable conveyor belt element corresponds to a standard function block in the controller. The assignment of the blocks to the individual conveyor belt elements follows a harmonized, standardized system of call-up parameters. It is also possible to assign conveyor belt elements to several manual areas or overlap these. When planning the transport layout, the employees in charge define the individual manual areas and the locations of the control panels. When creating the program for central control, the calls of the function blocks are then linked to the appropriate parameters. The layout stipulated by the PLC programmer for the control panels is then taken into account when creating the attendant projects. I NTE R P L AY O F P LC A N D VI S UA LI Z ATI O N The zenon automotive generator reads the required information from the equipment control programs automatically and can set many project properties independently this way. The wizard thus determines, for example, the number and type of projects for the control panels, reads the attendant conveyor system elements and adds them to the attendant equipment screens. The “zag” also identifies global settings for all projects and configures them in the individual projects. This includes, for example: – –

Display of name and status of the different load circuits Overview and status of the respective operating types of the control panels

– –

Setting the network addresses (PLC and control-panel addresses) Configuration of the message channel display

The message channel can be used for a detailed display of certain process devices or motor modules. The operator requests detailed data from the controller and it reports that data back for visualization. The type and content of the message channels is provided by the PLC programmer – the “zag” collects the necessary data from the controller program and creates the required operating elements for the user. U S E R - F R I E N D LY I NTE R FAC E With the help of tabs, the user interface of the wizard shows the respective current action of the “zag” with a clear overview. With each further processing step, a switch to the next tab is made automatically. The operator thus receives guidance and a comprehensive overview at the same time. All actions of the wizard are written to a log file for subsequent tracing or analysis. C E NTR A L DATA S TO R AG E The zenon automotive generator stores information from the PLC program in a central file. The actual control-panel projects are generated from the data saved therein. If the PLC program is to be amended at a later point in time, this file is used to make a comparison. Existing projects are only supplemented. In the current version of the wizard, the information is read from a STEP 7 program. The central file allows an expansion of the wizard for other controller types. In this case, only the program part would need to be amended accordingly for data recording and storage. The reading of the central file and the actual project creation can be reused.

“An actual example of zag in use: for the new A4 and A5 product range, we implemented 300 projects with five suppliers for the conveyor systems in the body construction area. A project runs on each control panel. An employee would need five hours per project for configuration without automated engineering. That’s a total of around 1,500 hours. With the zag, only around five hours plus subsequent visual corrections of around another five hours were necessary.” ERWIN-SEBASTIAN MEILINGER, AUTOMATION SYSTEMS PLANNER, FOR AUTOMATION SYSTEMS IN THE PAINT SHOP AND CONVEYOR SYSTEMS AREAS AT AUDI AG

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“The zenon automotive generator from COPA-DATA provides clear advantages. First, we save a considerable amount of time and therefore costs when configuring new equipment. Second, with the zag, we can guarantee that all projects are harmonized and free of errors. For example, no unnecessary variables are created, projects are streamlined and accurate. All in all, with the zag we were able to increase the quality of equipment configuration and increase productivity.” ERWIN-SEBASTIAN MEILINGER, AUTOMATION SYSTEMS PLANNER, FOR AUTOMATION SYSTEMS IN THE PAINT SHOP AND CONVEYOR SYSTEMS AREAS AT AUDI AG

S I M P LE WO R K WITH TH E “Z AG ” Once the “zag” has been started, the user configures the wizard. In doing so, he stipulates the name of the central fi le and selects the attendant STEP 7 program using a combobox. Once all required data has been read from the PLC program, it is saved in the fi le and displayed in groups with a clear overview using the “zag”. In this summary, all control-panel configurations stored in the PLC code are also visible and ready for project configuration. The wizard operator can now select which control-panel projects he wants to create. The wizard carries out the following steps when creating a project: 1. Entering of the global data into the template project, including for example the IP address of the controller, configuration of the load voltages and operating modes 2. Copying the template project and automatically applying it to all control-panel projects 3. Activating control-panel-specific variables and addressing them correctly 4. Adding conveyor system elements assigned to the respective control panel from the symbol library, into the operating screens and linking them to the corresponding variables 5. Adding and configuring load circuit and mode symbols necessary for manual operation 6. Configuring the message channel diagnosis screen 7. Setting control-panel address for Remote Transport and create zenon Runtime fi les 8. Done! The control-panel project is now ready to transfer data to the panel. The “zag” now automatically creates the manual operation screen, on the basis of the information read from the PLC program, and adds the attendant conveyer system elements into the operating screens of the control-panel projects. The person configuring the project can then move these elements to the correct position and also rotate them.

A tailor-made conveyor system layout is thus created if desired. It is of course also possible to subsequently amend or supplement projects with further conveyor system components, by means of an update function in the wizard. Some of our renowned customers in the automotive sector are already using the zenon automotive generator. It has now been operating successfully at AUDI AG for three years.

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Vid eo: S ave u p to 9 8% of engin eering t im e wit h t h e “ zag ” S c a n & Play!

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