November EMag 2023 by Launched

tbtech publication £9.99 tbtech.co STORIES INSPIRED BY MODERN LIVING. NOVEMBER 2023

Digitalisation Is the Future MANUFACTURING

May 2023

Meet your tbtech team.

JOE ALLEN

PAUL WHITTALL

MATT ROBERTS

Joe has vast experience and knowledge accumulated and honed as a New Business Development Manager and Relationship Manager. Responsible for generating new business opportunities, looking after the growth of the company and strategy, sourcing new ventures and managing the company.

Paul stops at nothing to innovate and create value for our customers. His mission is help those we work with to win in their markets. Passionate about delivering customer success and have had the pleasure of supporting many of the world’s leading technology brands for over 15 years.

Matt is Operations Manager at TBTech, he has spent the last 15 years working with multinational IT companies building campaigns, GTM strategies, leading both Sales and Marketing teams to achieve organisational goals. With a love of computer science, history, and psychology he is an advocate for change, operational efficiency and automation. Value across the business for all our customers.

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We have been working behind-the-scenes to elevate the readers experience.

ERIN LANAHAN Erin’s love for advertising and design has led her to Tbtech as the Media Marketing Apprentice. She loves exploring new skills and learning more about the tech sector and making sure the magazine is up to standards.

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FEATURED

Digitalisation: transition presents opportunity Natasha Avelange, Group XR Manager–Projects, at TNA solutions, looks at the drivers behind digitalisation in food processing and packaging and the value manufacturers can expect to gain by embracing the change Overcoming challenges is nothing new in the world of food production, but in recent years there has been more to deal with than expected. The global pandemic has led to shortages and supply chain breakdowns, and when coupled with the pressures added by the conflict in Europe these issues have only been magnified. In addition, there are challenges that have been building gradually and steadily over a longer period. Environmental concerns are more front of mind than ever before as climate change continues to advance, and both skilled and unskilled labour is increasingly difficult to find and retain across the industry. Whilst this all seems like a downhearted way to begin, what these challenges highlight is that the industry is in a transitional phase, which is being accelerated by rising energy and raw material costs. Processes honed over many years based on full employment and robust supply chains will inevitably have to change, but where manufacturers are driven to achieve efficiencies there are benefits to be reaped if changes are addressed in the right way. Transition – or change – presents opportunity, and the way to take advantage in a digital age is to leverage technological advances. In short, digitalisation is the way forward!

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By Natasha Avelange, TNA’s expert

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Embracing a digital future WHERE DO WE BEGIN? This is inevitably the first question that occurs, and the answer lies with a partner with the portfolio and expertise to advise from the outset and to deliver in the short, medium, and long term. OEMs have increasingly moved from the role of commodity suppliers to consultative partners, supporting customers as they adapt to evolving trends, and by working with an expert partner that is not only well-versed in digitalisation but that also has the capital equipment and software to support it in-house, the journey starts to become easier very quickly. Help is the operative word, and alongside it support, as making the decision to forge ahead with digital solutions can be daunting. However, once made the benefits offered by digital technologies are – in effect – endless and can be seen to deliver value very quickly. In the following sections we will highlight three of the most prominent examples of how digitalisation can make a positive impact, addressing not only the need for efficient energy

consumption and increased automation, but also how integrating technology can help to protect margins and therefore profitability. 1. End-to-End Control Having a complete operational overview and the ability to control it is key. IoT-based technologies such as advanced self-learning software, artificial intelligence (AI) and wireless connectivity protocols provide the digital functionalities necessary to deliver seamless integration between various line components – driving efficiencies in a range of areas. If we take a vertical form fill and seal system (VFFS) as an example, real-time protocols now come as standard which, along with smart diagnostics and remote connectivity, enable food producers to optimise their lines in real-time via detailed packaging performance reports. Should any challenges arise, the smart operating system and remote communication features within the system give operators access to targeted global servicing support to get production back up and running quickly and easily –

minimising downtime. Seamless, wireless integration between line components also enables operators to calibrate an entire line to produce almost any product type – which cuts changeover times dramatically. This has a tangible, positive impact in terms of line efficiency, as all factors that have the potential to slow down production can be minimised. In the production of potato chips, for example, blockages or errors in the conveying system can be communicated automatically to the seasoning, frying, and weighing equipment, which prevents product waste and alerts operators to the issue before it causes costly downtime or compromised batches. Modern food production facilities use several different layers of control and monitoring protocol, structured as follows: 1. Enterprise resource planning (ERP) software – sets out goals at a company-wide level 2. Manufacturing execution systems (MES) – manage bigpicture production planning

3. Supervisory Control and Data Acquisition (SCADA) systems – supervise production lines while in use 4. Programmable logic controllers (PLC) – programme individual equipment operation 5. Actuators, sensors and Human Machine Interface (HMI) – collect the real-time data that feeds the entire process. The performance data captured from the above can be used to set accurate, bespoke production targets and, with this information at their fingertips, site managers can establish an effective predictive or preventative maintenance strategy – a valuable, proactive approach to avoiding unplanned stoppages 2. Remote Support The development of digitally enhanced remote support tools has been accelerated in recent years, with remote maintenance solutions harnessing the power of augmented reality (AR). Operators now have the ability to share exactly what they see with technicians and to receive clear and accurate instructions as if those technicians were standing

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right next to them. The accessibility of experts via AR technology means producers have access to a wealth of options that would ordinarily require a costly onsite visit – such as the calibration of lines for different bag sizes or packing designs, tuning-up existing equipment and even commissioning new solutions. This ability dramatically cuts the potential downtime that can occur due to geographical boundaries, and allows brands to build lines based on agility, flexibility and efficiency wherever they are in the world. VR headsets, too, deliver multiple benefits. For example, they allow manufacturers to create a digital twin – a carbon copy of their physical production line in digital format – which operators can then use to test potential settings. The virtual imitation allows the identification and eradication of issues prior to implementing the new settings on real-world equipment, potentially saving hours of unscheduled downtime. These advanced digital line representations also allow brands to develop training programmes

to educate teams quickly and effectively. Operators can practice key processes on true-to-life virtual machines, which enables them to understand complex systems without exposing the line to real-time delays or errors that would ordinarily lead to delays. Research shows that this form of training can deliver an 80% retention rate 12 months after the initial training programme, proving that remote servicing and AR-based maintenance tools have far-reaching benefits outside of downtime risk mitigation. 3. Traceability, clean labels and reduced waste Embracing digitalisation can also lead to a boost in terms of brand reputation, building consumer confidence and improving producers’ sustainability credentials. In the field of food safety for instance, wirelessly connected barcode scanners, date code assurance tools and metal detection equipment can be seamlessly integrated into the production line. Once installed, they automatically verify product batches, confirm ‘use -by’ dates and continuously scan for foreign

bodies, pinpointing the source of contamination within the product stream. This automated oversight speeds up the food safety assurance process and removes the risk of human error – ensuring each and every pack meets consumers’ – and regulatory bodies’ – exacting standards. From a consumer perspective, GlobalData’s 2022 Analysis on Sustainability & Ethics points out that, in an age of connectivity, the digital landscape is fuelling the emergence of more empowered and informed shoppers. Producers must remain mindful of this fact, but can leverage digital food processing and packaging equipment to help build a stronger sustainability story around their products. A good example of this is the pre-set recipe options – included as standard with the latest market-leading seasoning equipment. These integrated programs help reduce waste and improve batch-consistency by ensuring only the exact amount of seasoning is used for each specific product type. Taking this concept further, digitally enhanced operating systems

help conserve more than just seasoning ingredients. Productin-seal-detection (PISD) solutions can be incorporated into VFFS packaging systems to monitor seal integrity and flag when specific packs become compromised. This ultimately leads to less waste, greater consumer satisfaction and products that are as good for the planet as they are for producers’ bottom lines. SIMPLY REVOLUTIONARY Whilst the prospect of adopting smart digital technologies can be overwhelming, especially in the face of an uncertain economic outlook, the simple truth is there are no areas of the food production process that don’t stand to benefit from digitalisation. The key responsibility for OEMs is to cut through the complexity and to make digital technologies not only more attractive, but more accessible to food brands. Empowered with straight-forward advice from an expert processing and packaging partner, manufacturers have nothing to lose by going digital, and everything to gain.

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FEATURED

Unlocking the potential of digital manufacturing: how AI is changing the game

The digital revolution has disrupted nearly every industry, and manufacturing is no exception. With advancements in artificial intelligence (AI) and the Internet of Things (IoT), the manufacturing sector is undergoing a transformative shift, unlocking new possibilities, and redefining traditional processes. Before we dive deep into the topic it’s important to understand what digital manufacturing is. Digital manufacturing refers to the integration of digital technologies into the manufacturing process, encompassing everything from design and prototyping to production and distribution. AI and IoT play a crucial role in this transformation by providing manufacturers with valuable insights, automation capabilities, and realtime data.

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By Dr Narayanan Ramanathan, Global Head of Digital Manufacturing Services, L&T Technology Services

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Embracing a digital future HARNESSING THE POWER OF AI Artificial intelligence (AI) has the capability to usher in a new era of digital transformation, presenting immense potential to revolutionise industries, enhance efficiency, promote sustainability, and engage the workforce. While the impact of AI applications in manufacturing and value chains is recognised, there remains untapped potential in fully harnessing their deployment and there are various ways in which manufacturers can harness the full potential of AI Powered by machine learning algorithms, AI has revolutionised several aspects of manufacturing. One of its key contributions is predictive maintenance. By analysing data from IoT sensors embedded in machinery, advanced algorithms can predict and detect equipment failures before they occur, allowing manufacturers to schedule maintenance proactively. This not only reduces downtime and production losses but also extends the lifespan of machines,

optimising resources and reducing costs. Another area where AI is making a significant impact is in quality control. Traditional quality control processes involve manual inspection, which is timeconsuming, subjective, and prone to errors. AI-powered computer vision systems can automate the inspection process, analysing images or videos of products in real-time to detect defects, inconsistencies, or anomalies. This ensures higher accuracy, faster inspection times, and improved product quality, resulting in higher customer satisfaction and reduced waste. AI is helping even in Product Design phase for improving the Design for Manufacturing (DFM) and Design for Serviceability (DFS) by studying Prototypes and 3D models, thereby determining the optimized way of manufacturing a product. Decisions made at the design stage helps in faster workflows by avoiding repetitive manual task. AI helps designers and engineers solve complex problems by

creating intelligent algorithms.

implementing the same.

Additionally, AI enhancing the efficiency of production planning and optimisation. By analysing historical data and real-time information, AI algorithms can optimise production schedules, minimise bottlenecks, and allocate resources more effectively. This enables manufacturers to streamline their operations, reduce lead times, and respond quickly to changes in demand. AI-powered optimisation can also help in minimising energy consumption and reducing the carbon footprint of manufacturing processes, contributing to sustainability goals.

(EM)POWERED BY IOT

AI is also assisting manufacturers to capture their workers’ tribal knowledge and aiding in democratising them for the benefit of the greater good - by recommending the optimal settings for the various scenarios and the products to be manufactured, suggesting the Next-Best-Action (NBA) for process failures and equipment failures, and by implementing closed loop systems in getting feedback from the operators &

The manufacturing sector is under constant pressure to reduce costs, and at the same time to boost efficiency and productivity. The Internet of Things (IoT) has emerged as a potential solution for manufacturers. IoT devices are revolutionising the way machines and systems communicate and interact with each other. By connecting physical devices to the internet and enabling them to collect and exchange data, IoT is creating a network of interconnected devices and systems, forming the backbone of smart factories. Through IoT, manufacturers can monitor and control their production processes in realtime. IoT sensors embedded in machines, equipment, and products can collect data on various parameters such as temperature, pressure, vibration, and performance metrics. This data can be transmitted and analysed instantly, providing manufacturers with valuable

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insights into their operations. IoT can also help manufacturers in achieving greater visibility and transparency across the entire supply chain. Real-time data on inventory levels, production rates, and demand fluctuations allow manufacturers to optimise their inventory management, reduce stockouts, and improve order fulfilment. IoT-enabled tracking and tracing also enhance supply chain traceability, ensuring compliance with regulations and standards. For example, a global hi-tech manufacturer implemented a component content management system (cCMS) which optimised productivity and improved the overall efficiency of content management & translation processes and also helped the company in saving $6Million in 5 years. IoT is also enabling the concept of smart products. Through embedded sensors and connectivity, manufacturers can collect usage data and feedback from customers, gaining valuable insights into product performance, customer preferences, and

usage patterns. This information can be used to drive product development, improve features, and offer personalised experiences, thereby enhancing customer satisfaction and loyalty. Overcoming the barriers to an AI and IoT enhanced future However, along with these opportunities, there are also challenges that need to be addressed. The first and foremost challenge in exploiting the potential of AI is in establishing the Trustworthy AI platform for critical systems and improving the trust quotient over the period. Notably, there are international entities & governments who are helping in setting up Ethical AI systems, and popular frameworks includes “Draft Ethics Guidelines for Trustworthy AI by European High Level Expert Group on AI” and “AI for Europe by European Commission”. Adopting the framework guidelines and technologies (FEAS – Fair, Explainable, Auditable and Safe) will help in setting up

and improving not only the trust quotient, also improves Compliance and legal factors as well. One major concern is data security and privacy. According to a research, manufacturing is the most targeted sector by cyberattacks. With the massive amounts of data being generated and transmitted in digital manufacturing, ensuring the protection of sensitive information, and guarding against cyber threats becomes critical. Robust cybersecurity measures and protocols need to be implemented to safeguard manufacturing operations and intellectual property. In 2022, the number of ransomware attacks targeting industrial infrastructure experienced a significant increase, effectively doubling from previous years. These attacks pose a grave threat to the smooth operation of supply deliveries, potentially leading to a systemic impact. The disruptive nature of cyberattacks has the power to cripple businesses and disrupt supply chains, thus negating the benefits derived from digitalisation efforts.

Consequently, financial and productivity losses are incurred, accompanied by reputational damages. The success of digital manufacturing transformation endeavour depends on effective change management practises. It can be a difficult and timeconsuming procedure to make significant modifications to current manufacturing processes. This is especially true when it comes to making critical changes for complex discrete and process manufacturers. Identification of the digital champion, establishing the clear change management story, developing a cross functional team and deploying incremental digital updates are the key to establish successful change management. Moving to Rollout from the pilot stage continues to be a significant barrier for most manufacturing organisations. In fact, there is a wider gap between piloting and rollout than between perceived relevance and piloting, indicating that scaling is more difficult than getting things started. Prioritizing the use cases based on Return-on-value (ROV), ease of

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FEATURED

The smart factory setup: The smart next move for manufacturers Digital empowerment is the new success gauge across the manufacturing sector. It requires integrating digital and physical systems, advanced visibility, and more flexibility, all of which bring improved efficiency and decreased costs. To enhance each element of manufacturing operations requires organizations to be able to leverage data from the factory floor to the client call center and to the C-suite. Enter the smart factory, its adoption is on the rise. The global smart factory market size was evaluated at USD 129.74 billion in 2022 and is expected to hit around USD 321.98 billion by 2032, growing at a CAGR of 9.52% from 2023 to 2032. Here Kevin Bull, Product Strategy Director at Columbus UK, demonstrates how manufacturing businesses can

Gartner describes the smart factory as a ‘concept used to describe the application of different combinations of modern digital technologies to create a hyperflexible, self-adapting manufacturing capability. Smart factories are an opportunity to create new forms of efficiency and flexibility by connecting different processes, information streams, and stakeholders (frontline workers, planners, etc.) in a streamlined fashion.’

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By Kevin Bull Product Strategy Director Columbus UK

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The smart factory setup: The smart next move for manufacturers SO, ARE MANUFACTURERS READY TO MAKE THE SMART MOVE? Digital transformation is an integral part of the smart factory setup as Industry 4.0 technologies such as IoT sensors, ERP, cobots, and AI are unlocking new manufacturing efficiencies. But with new technology innovations always on the horizon, manufacturers are among the businesses most susceptible to more digital transformation changes – and they seem to know it. A recent report, found 63% of manufacturers are focusing on increasing manufacturing agility over the next 12-24 months – and this is where the smart factory comes in. But although many manufacturing businesses have already used automation, smart factories go one step further and operate automatically. Smart factories are more adaptable than their predecessors because they embrace contemporary technology, which allows them to change in real-time. The endresult? A smart factory ensures that every link in the value chain is

connected to inform manufacturing decisions with no delays and zero defects. And the critical components to creating a smart factory are: data-driven insights, automated demand forecasting, and an effective customer experience and engagement strategy – all underpinned by cutting-edge technologies. 1. The data building blocks – integrating smart systems with smart systems is a win-win for the smart factory Smart manufacturing is all about delivering the right information to the right people at the right time. A manufacturer’s journey relies on trusted data-driven insights but data management remains one of the biggest time sinks in any organizations, especially when manufacturers rely on legacy systems that can’t effectively integrate with other businesses systems to share data. The accurate and automatic flow of data between systems is crucial to increasing efficiency and production. This means it’s essential to have a seamless

horizontal integration between operational systems and vertical integration through connected manufacturing systems, as well as end-to-end, holistic integration through the entire value chain. The first stage of unlocking the data goldmine is to analyze the business processes that are causing the most pain, and then to analyze the data that flows through them to identify areas of inaccuracy, duplication, and incompleteness. From here, manufacturers can begin to build a data strategy that reduces waste and optimizes the data value stream with smart manufacturing technologies. Modern data collecting and analytics tools that integrate with each other can be effective in maximizing productivity. Take the example of integrating a CRM and ERP system – together these smart systems can eliminate data siloes, minimize manual work, and provide manufacturers with a 360-degree view of customer buying habits, order history, and preferences. This will help manufacturers deliver more personalized experiences and track changes in

customer behavior to determine opportunities for future growth. 2. Demand forecasting goes proactive and predictive, and opens the door to production optimization The most effective way manufacturers can operate more efficiently, increase production, and increase margin is to shift from a reactive operating model to a proactive, predictive one that leverages collective data. Actionable insights from AI, machine learning, and IoT outputs provide a connected digital feedback loop which enables realtime operational optimization. This ensures organizations have the ability to proactively leverage this new-found knowledge across the entire value chain. Demand forecasting is used to anticipate demand with enough time to manufacture the right amount but often the problem is capacity, demand, and cost aren’t always known parameters. Variations in demand, supplies, transportation, and lead times create uncertainties which can have widespread effects on

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production scheduling, inventory planning, and transportation – and this is where machine learning tools can help manufacturers produce the exact amount of product to meet demand. No more. No less. Accurate demand forecasting with machine learning tools tries to predict future demand for a product or service in a supply chain by relying on economic and consumer conditions in the marketplace. Demand forecasting looks at historical data, market trends, missed sales, economic conditions, competitors’ actions, and a variety of other factors to anticipate future customer behavior. It’s the first step in production planning and a key requirement to addressing uncertainties in supply chains. Manufacturers can use these insights to make more informed decisions about production, inventory, and staffing – avoiding shortages or overages, which can be costly and damaging to the business. Accuracy in forecasting significantly reduces operating costs and makes businesses more efficient, more profitable, and better equipped to deal

with periods of unpredictable uncertainty.

customer – but the technology advantage doesn’t stop there.

3. The CX value add – it’s an organization-wide effort

THE SERVITIZATION OF MANUFACTURING UNLOCKS NEW CUSTOMER CENTRICITY OPPORTUNITIES

A connected supply chain is not truly effective if the connectivity ends with the product. Digital customers are now more connected and empowered than ever before. With so many options available at their fingertips, customers won’t hesitate to take their business elsewhere if they feel their needs aren’t being met. Unsurprisingly, research found that 63.73% of manufacturers placed creating a seamless customer experience as a top business priority. It’s up to manufacturers to rethink customer experience and engagement (CXE) approaches – so what smart manufacturing tools can help meet this pressure? Digital technologies such as a customer relationship management (CRM) system can help manufacturers not only deliver high quality products but also provide exceptional customer experience to meet the higher expectations of the new age

As with other industries such as retail, the buyer’s journey has moved online and it’s up to manufacturers to meet customers where they are and add value through content and personalized experiences, with all digital experiences offering high quality interactions. Manufacturers don’t need to digitize the whole customer experience – simply digitizing product catalogues can be a step towards improving customer experience. Essentially, it’s about giving customers more autonomy such as allowing them to view accurate stock levels, configure product functionalities, and customize pricing. Due to the ever-lowering price of IoT sensors, state-of-the-art mobile devices, and cloud-based statistics aggregation, manufacturers can enhance service standards and margins by means of providing

remote tracking and proactive maintenance that complement damage/restoration assist. REINVENT MANUFACTURING 4.0 THE SMART WAY With so many cutting-edge technologies at play, smart factories are able to operate at a level of speed, precision, and flexibility that traditional factories simply can’t match. It’s all about emerging technologies coming together to take manufacturing into a new era dominated by connectivity, autonomy, and visibility. With the right digital tools, and a refreshed customer experience mindset, manufacturers are certainly ready to unlock the new levels of efficiency and productivity that are the stock-in-trade of smarter factories!

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Decarbonising industrial heat: The technologies of today and tomorrow

Across an average year, industrial carbon emissions account for around 29% of global greenhouse gas (GHG) output. This makes it one of the world’s biggest carbon emitters. A large part of the reason for this is the industrial sector’s need for heat, which is almost entirely generated by fossil fuels. Heat makes up two-thirds of industrial energy demand and almost one-fifth of global energy consumption.

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By Paul Miller, Director, Drax Energy Solutions

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Decarbonising industrial heat: The technologies of today and tomorrow PDecarbonising industrial heat is, therefore, a critical part of our global strategy against climate change. The trouble is that it remains a hugely complex challenge due to the diverse nature of the types of heat required. Fortunately, there’s a growing number of solutions on the market, including emerging technologies that can tackle temperature requirements of over 1,000°C. In this article, we’ll explore these heat decarbonisation solutions in greater detail to help manufacturers determine the best route for them on their journey to net zero. UNDERSTANDING THE CHALLENGES OF DECARBONISING INDUSTRIAL HEAT Manufacturers use heat across a wide variety of processes, meaning the temperature and quality of the heat required can vastly differ from application to application.

For example, food and drinks manufacturers typically need low-temperature heat for things like drying and pasteurisation, whereas metal and glass manufacturers need hightemperature heat for melting and material transformation. For this reason, it’s crucial that heat solutions are compatible with the various products and process conditions. Generally speaking, low-grade heating is easier to decarbonise than high-grade heating as more mature solutions are available. May solutions for high-temperature requirements are still in the early stages of commercialisation. However, it won’t be long before these are made available. What’s more, replacing existing equipment and infrastructure can be capital-intensive, particularly when these assets haven’t yet reached the end of their lifecycle. Energy assets typically have a long life, so manufacturers may be reluctant to replace them.

WHAT SOLUTIONS AND TECHNOLOGIES ARE AVAILABLE TO DECARBONISE HEAT? Several technologies, such as solar thermal systems, geothermal heat pumps, biomass boilers, and wind-powered heat systems, can provide sustainable and low-carbon heat for industrial processes. Ongoing research is also aiming to address the demand for high-temperature solutions. At Drax, we can help you understand how to best integrate and leverage these new technologies effectively while supporting the UK’s wider push towards net zero.

during winter, cutting energy costs. It can also be installed in a new building at a relatively low cost and has a 20–25year life expectancy. However, its efficiency depends on the deployment location. Heat pumps – currently the only available, scalable, and proven technology for fully decarbonising heat and hot water. Heat pumps can efficiently generate heat without direct carbon emissions. However, while they’re an efficient solution for low temperatures, they’re less effective for mediumto-high temperatures.

Shallow /deep geothermal - can effectively generate hot water but is limited to some regions of the country and involves complex and often expensive drilling operations.

Biomass and waste boilers – in additional to being an excellent source of renewable energy, biomass can also be used to provide low-carbon or carbonneutral heat. Biomass boilers and combined heat and power (CHP) systems produce heat and electricity using organic resources like agricultural waste.

Solar thermal - an excellent low-carbon technology that is underused in the UK. Solar thermal systems can absorb heat even

Biogas/biomethane - can turn waste products into a sustainable and cost-effective source of heat and power. However, availability

Here are a few examples:

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in the UK is limited, and the source of feedstock needs to be carefully considered to ensure it’s truly carbon efficient. WHAT ARE SOME OF THE EMERGING SOLUTIONS TO DECARBONISE HEAT? Several promising technologies are currently being developed to decarbonise heat within manufacturing. These include hydrogen, electroprocessing, and carbon capture, use and storage (CCUS). Each of these solutions will likely play a significant role in decarbonisation and is suitable for different temperatures and applications. Hydrogen - not likely to be used for general heating and hot water in buildings due to scarcity, cost, and inefficiency concerns. However, it shows promise for very high-temperature processes where no other alternatives currently exist. Electroprocessing – Direct electricity can be applicable in specific circumstances, such as short-duration and very high-

temperature processes. It can achieve zero carbon emissions but may be less efficient than other technologies for longer-duration heating. Carbon capture, use and storage (CCUS) – an emerging technology that holds huge promise. Once fully deployed at scale, CCUS is likely to play a central role in extensive district heating or power generation. To support a zero-carbon, lowercost energy future and meet the goal of being carbon negative by 2030, Drax is developing Bioenergy with Carbon Capture and Storage (BECCS) technology. This transformative technology will contribute to decarbonising whole industries and organisations by enabling them to achieve negative emissions and address climate change. HOW LIKELY IS IT THAT THE UK WILL SUCCEED IN DECARBONISING HEAT IN TIME FOR THE 2050 DEADLINE? The industry faces a significant challenge in decarbonising heat

due to the enormous scale of heat used for processes requiring high temperatures. Unfortunately, this is an area of carbon emission reduction that has historically been neglected. However, continuous advancements in low-carbon heating technologies including enhanced efficiency and availability are changing all of this. With the right level of urgency and investment, it’s highly possible that we’ll succeed. In the meantime, manufacturers should focus on developing a robust strategy which identifies the steps they can take today and the opportunities for the future.

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Cybersecurity in the Gaming Industry MONEY! The word alone evokes excitement, and no other industry combines recreation, banking, tourism, risk, hospitality, retail, surveillance, and online app’s like the gaming industry. Gambling and associated business’ is massively complicated, and given the amount of money involved, is one of the most targeted in the cybersecurity industry. The gaming industry today operates around four main revenue centres. First, are the traditional casinos, where people exchange cash for proprietary chips or tokens and bet on any number of sports, card games, slot machines, etc. Second, surrounding a modern casino’s gaming floor are high-end retail and food outlets; and while not specific to the act of gambling, the retailers like to associate high-value brands with the image of luck, wealth, and success arising from gaming.

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By Gary Kinsley, Author of 2 cybersecurity books: Attack Vector and Deadly Protocol

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Cybersecurity in the Gaming Industry Also attached to many casinos are the third source of revenue, hotels. Typically, operated under license by branded hotel chains’, the casino operators own the freehold on the hotels and again align the ‘wealth experience’ for gaming tourism. Many hotel rooms will market and provide easy ‘virtual’ on-line gaming for patrons who’d rather not leave their rooms to game, but still enjoy the experience of gambling tourism. Lastly, the fourth income source is on-line gaming. Varying based on demographics, online gambling whether it be bingo for the elderly or action games for teenagers involves paying for the experience of the game, and the chance of winning, status, virtual rewards, and money. WILLIE SUTTON A gaming organisation will often be a combination of these four sources of revenue, and cybersecurity must be viewed holistically from the multiple attack vectors arising from each. Increasingly, on-line gaming companies are adopting

bricks-and-mortar venues; and traditional casinos are building shopping malls with attached hotels. Gaming, like banking, is an extremely heavily regulated industry. It’s also one of the most targeted for cybercrime. A reporter once shouted to Willie Sutton, the infamous American bank robber, “Hey Willie, why do you rob banks?” “Because that’s where the money is!” Was Willie’s retort. The reality is that the gaming industry is under constant attacks from cyber criminals. The challenge is the number of attacksurfaces to which the gaming industry is exposed. Online gaming app’s can be exploited by hackers to gain unauthorized access, manipulate gameplay or compromise players’ data. Given the relative newness of the industry the focus on DevSecOps is mandatory and an imbedded part of the game development process. Traditional casinos are hard to protect. Take the simple example of the hotels. Hotels have multiple

online applications such as reservation systems, Point-of-Sales stations, Wi-Fi everywhere (with at least one network open to the public), surveillance systems, and many automated building elements such as heating, aircon, physical access such as key cards, and many staff members for whom to validate access controls and permissions. Moreover, if the hotels networks are also attached to the retail shops, as part of the shopping mall encircling the gaming floor, and then the networks of gaming machines, and the building’s critical infrastructure, many operating on proprietary protocols, the cybersecurity risk becomes multidimensional. A breach anywhere could lead to command and control being established and a hack in one part of the operation could then expose vulnerabilities in others. Attempting to steal money is traditionally the bad actor’s objective, but increasingly this is cryptocurrency focused, and delivering ransomware or a DDOS attack the easier alternative.

Surveillance and licensing. As a casino CISO recently told me “…if, for example, our retail POS systems is breached and customers credit card credentials are stolen, it’s embarrassing, it’s awkward, people will be fired, and we will pay a fine. But the business will continue. However, if the surveillance cameras on the gaming tables are hacked and disabled, we must close the tables. If the tables close, and we can’t game, we lose our gaming license. That will kill our business.” TYPES OF CYBERATTACKS ON GAMING. For this reason, a gaming organization will often segment networks and have air gaps (or air walls) between critical networks. Surveillance cameras will often be isolated, with redundancy designed in for the network itself, but also for power supplies. Furthermore, critical infrastructure must be protected. Power supplied could be targeted for a DDOS attack, likewise air-conditioning systems for a casinos data centre

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would have the same effect. Man-in-the-middle (MitM) attacks are commonplace in venues with high flow of people such as the shopping malls, gaming floors, and hotels. These allow attackers to intercept communications between clients (such as gamers) and servers, again to manipulate or exfiltrate data. Unlike a secure office building, the difficulty of authenticating guests of retail shops, and hotels is impossible, thus making the network security the first line of cyberdefences. The growth of on-line gambling (globally a US$281 billion business in 2023) is the fastest sector with an estimated 13% YoY growth. Mobile devices are the most common interfaces, hence securing gaming applications is paramount. Common attack vectors for on-line gambling include the following: Buffer Overflow: Where data written to the buffer exceeds capacity. This can potentially lead to a code execution or privilege escalation.

SQL injection: Attackers can insert malicious SQL code into a game’s database queries allowing access to sensitive data or modify the database. Cross-Site Scripting (XSS): Where malicious scripts are injected into web-based games, which can then be executed in players’ browsers leading to data theft or session hijacking. Remote Code Execution: Where a game’s server-side code is vulnerable to exploit allowing other code to be executed. DLL Hijacking: Where attackers replace legitimate game Dynamic Link Libraries with malicious ones. Authentication Bypass: By exploiting flaws in the gamer’s login process’s, attackers can access user accounts without proper credentials. Denial of Service (DDOS): Attacks where gaming or application servers are overwhelmed with traffic disrupting gameplay for legitimate players. These attacks are not unique to on-line betting

as discussed above but are technically relatively easy to execute for bad actors. HOW CAN THE GAMING INDUSTRY PROTECT ITSELF FROM CYBER-CRIME? Traditional casinos have long established protocols for physical security. These are now having to be extended for on-line gaming, and the extended physical elements of shopping malls and hotels. Often a breach in one can expose vulnerabilities in other parts of the business. Anti-money laundering laws and data privacy means the consequences of a casino being breached may not simply be embarrassment and manageable monetary cost. Building sophisticated Security Operations Centres are commonplace in the gaming world, but incorporating Buildings Assurance and DevSecOps as functions are key as bad actors look to these less traditional vectors of attack.

SO WHAT CAN WE DO? As the threat landscape continues to evolve, cybersecurity consultants like CyberQ Group continue services of transforming your business to be cyber resilient. Services such as vulnerability assessments and penetration testing are key to the gaming world, as is building assurance (testing systems such as aircon, power supplies, surveillance cameras, proprietary protocols like SCADA, etc), and continuous breach detection and cyber simulations. Get in touch with us now to start safeguarding your digital future.

May 2023

Carbon Reporting and Bureau Services: essential to tracking net-zero progress In recent years, businesses have become acutely aware of the need to invest their time into carbon reporting, not least because of increasing expectations of reporting activities within supply chains and for their customers. For instance, the Climate Change Act 2008 (2050 Target Amendment) Order 2019,

May 2023

By Paul Rekhi, Head of Carbon Services Advantage Utilities

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Carbon Reporting and Bureau Services: essential to tracking net-zero progress “If you can’t measure it, you can’t manage it and therefore you can’t reduce it” But here’s what businesses need to consider: in order to reduce emissions, you first have to map emissions. After all, if you can’t measure it, you can’t manage it and therefore can’t reduce it! That’s why a clear strategy is so fundamental. But whilst 82% of UK businesses have set targets to reach net-zero before 2050, the majority still have a lack of visibility over their day-to-day operations. Research from the British Chambers of Commerce also shows that fewer than 10% of SMEs in the UK fully understand what the net-zero target means for them. This is what continues to stifle progress today. A BIG OPPORTUNITY: CARBON REPORTING Having said this, there is a significant opportunity available to businesses through carbon reporting. A carbon reporting platform - a method of managing data across all three emissions

scopes as well as facilitating supply chain reporting - is fundamental to facilitating the planning, tracking and reporting of businesses’ GHG emissions. And it’s this that allows them to progress fastest towards the ultimate goal of net-zero. There is also the added benefit that such a platform enables maximum collaboration between businesses and their supply chain to tackle the most significant and complex part of its carbon footprint - indirect scope 3 emissions. The benefits of employing Carbon Reporting are significant, not only enhancing working relationships with key retailer customers and suppliers, but also improving stakeholder engagement, fostering carbon neutrality and cost efficiencies are also possible. This means businesses can leverage the technology to not only reduce emissions, but also to reduce their energy bills and safeguard their reputation too. The detailed insight into business’ energy use is unmatched, enabling businesses to reduce consumption of expensive and pollutive non-renewable sources of energy such as energy

from the National Grid, making much-desired carbon and energy savings in the process. A BUREAU SERVICE BOLSTERS BUSINESSES CONFIDENCE Businesses should also not forget the immense value of a bureau service in giving additional confidence to businesses on their energy bills. The purpose of a bureau service is to validate bills and automatically highlight billing errors in the process via 100 checks which are carried out via the system. This technology is therefore crucial to measuring current bills and ensuring that no irregularities occur - and these are surprisingly common. In the event of overpayments, businesses can then make energy savings. Accessible through an online portal, businesses are empowered through better data on topics including their bills, their consumption, and carbon emissions. But by using carbon reporting in combination with this, businesses can better understand their needs and energy use so that bespoke

solutions can be implemented, thereby maximising carbon offsetting and reduction. However, to further boost net-zero progress, making energy savings in the process, businesses should implement the ‘Carbon-Ethics Cycle’: a five-step process through which businesses can continually make carbon reductions and energy savings by reporting benefits in terms of costs, reputation and brand value in the process. THE CARBON-ETHICS CYCLE: A ROADMAP TO NET-ZERO 1. Understand For businesses, the journey first begins with understanding their goals, targets, aspirations, budgets and timescales. This is what informs their strategy which will enable the most significant reduction in emissions. 2. Measure/Certify Next, businesses should then benchmark their scope 1, 2 and elements of scope 3 emissions, giving them valuable insight into both upstream and downstream energy usage and carbon

May 2023

production. Scope 1 emissions refer to those which have been directly produced by an organisation, such as their vehicles and facilities. Scope 2 emissions include indirect upstream emissions from purchased electricity and heating, via the National Grid for instance. Scope 3 emissions include those that organisations are indirectly responsible for up and down their value chain, such as purchased goods and services, transportation and distribution, commuting and business travel, investments and more. Using a carbon accounting platform is crucial to understanding the biggest causes and areas of emissions. This also means businesses can reach out for full independent certification and documentation, giving businesses the edge in their ongoing journey towards net-zero. 3. Consult By reaching out to industry experts, businesses can strategise and uncover the most effective ways to reduce their carbon footprint by using the latest market technologies. These include solar,

EVs, ground source pumps, and voltage optimisation to name a few. 4. Reduce/Offset In order for businesses to achieve their net-zero goals and whilst plans are put into place, ethical offsetting through carbon credit programmes may also be required for where carbon cannot be reduced or removed due to the technology not being available yet. Through calculating scope 1 and 2 emissions, businesses can then understand the amount of carbon they are producing, opening the door to International Carbon Credit programmes to reduce and offset emissions. 5. Report/Re-certify Businesses should re-measure and re-certify their carbon emissions alongside any credits and neutrality services on an annual basis - completing and restarting each cycle in the process.

To conclude, by using both a bureau service and utilising

carbon reporting, businesses can enhance their working relationships with key retailer customers and suppliers, improve stakeholder engagement and foster carbon neutrality and cost efficiencies in the process. These two services are also the most important tools for businesses in achieving net-zero, and by following the Carbon-Ethics Cycle in combination with these two technologies, there are still significant gains to be made.

May 2023

Will your network let down your AI strategy? As companies start to evaluate how they can use AI effectively, there is a clear need to ensure your network is up to the challenges of AI first. AI applications are going to require your data to be easily accessible and your network will need to be able to handle the huge compute needs of these new applications. It will also need to be secure enough at all points of access for the different applications to end users’ different devices. If your network isn’t reliable, readily available and secure it is likely going to fail.

May 2023

By Rob Quickenden, CTO, Cisilion

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The Gaza Conflict – does it affect your cybersecurity? In Cisco’s 2023 Networking Report 41% of networking professional across 2,500 global companies said that providing secure access to applications distributed across multiple cloud platforms is their key challenge, followed by gaining end-to-end visibility into network performance and security (37%). SO, WHAT CAN YOU DO TO MAKE YOUR NETWORK AI READY? First, you need to see AI as part of your digital transformation, then you need to look at where you need it and where you don’t. Jumping on the bandwagon and implementing AI for the sake of it isn’t the way forward. You need to have a clear strategy in place about where and how you are going to use AI. Setting up an AI taskforce to look at all aspects of your AI strategy is a good first step. They need to be able to identify how AI can help transform your business processes and free up time to focus on your core business. At the same time, they need to make sure your infrastructure can handle your AI

needs. Enterprise networks and IT landscapes are growing more intricate every day. The demand for seamless connectivity has skyrocketed as businesses expand their digital footprint and hybrid working continues. The rise of cloud services, the Internet of Things (IoT), and data-intensive applications have placed immense pressure on traditional network infrastructures and AI will only increase this burden. AI requires much higher levels of compute power too. The challenge lies in ensuring consistent performance, security, and reliability across a dispersed network environment. USE HYBRID AND MULTICLOUD TO DE-SILO OPERATIONS According to Gartner’s predictions, by 2025, 51% of IT spending will shift to the cloud. Underscoring the importance of having a robust and adaptable network infrastructure that can seamlessly integrate with cloud services. This is even more important with AI as it needs

to access data from different locations and sources across your business to be successful. For example, AI often requires data from different sources to train models and make predictions. A company that wants to develop an AI system to predict customer churn may need to access data from multiple sources such as customer demographics, purchase history and social media activity. IT teams need to make sure that they are using hybrid cloud and multi-cloud to de-silo operations to bring together network and security controls and visibility and allow for easy access to data. Where businesses use multiple cloud providers or have some data on-premise, they need to be reviewing how that data will be used and so how to access it across departments.

INSTALL THE BEST SECURITY AND NETWORK MONITORING It’s clear that as we develop AI for good, there is also a darker side weaponizing AI to create more sophisticated cyber-attacks.

May 2023

Businesses need end-to-end visibility into their network performance and security and to be able to provide secure access to applications distributed across multiple cloud platforms. This means having effective monitoring tools in place and the right layers of security – not only at the end user level but also across your network at all access points. Being able to review and test the performance of your SaaS based applications will also be key to the success of your AI solutions. AI requires apps to work harder and faster so tasting their speed, scalability and stability, and ensuring they are up to the job and can perform well under varying workloads is important. Secure Access Service Edge The best way to ensure your network security is as good as it can be is to simplify your tools and create consistency by using Secure Access Service Edge (SASE). This is an architecture that delivers converged network and security as service capabilities including SD-WAN and cloud native security functions such as secure

web gateways, cloud access security brokers, firewall as-aservice, and zero-trust network access. SASE delivers wide area network and security controls as a cloud computing service directly to the source of connection rather than at the data centre which will protect your network and users more effectively. SD-WAN connectivity If you haven’t already, extending your SD-WAN connectivity consistently across multiple clouds to automate cloud-agnostic connectivity and optimise the application experience is a must. It will enable your organisation to securely connect users, applications and data across multiple locations while providing improved performance, reliability and scalability. SD-WAN also simplifies the management of WANs by providing centralised control and visibility over the entire network. As we head towards the new era of AI, cloud is the new data centre, Internet is the new network, and cloud offerings will dominate applications. By making sure your

network is AI ready, by adopting a cloud-centric operating model, having a view of global Internet health and the performance of top SaaS applications, IT teams will be able to implement their company’s AI strategy successfully.

May 2023

The critical role of data integrity in generative AI According to government research, around one in six UK organisations are currently implementing at least one application of artificial intelligence (AI), with usage expected to increase at a rapid pace. In fact, it’s predicted that the AI market will add approximately 800 million pounds to the UK economy by 2035.

May 2023

By Anjan Kundavaram, Chief Product Officer, Precisely

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The critical role of data integrity in generative AI These findings suggest that, more than ever before, business leaders need to assess the data flowing throughout their organisation, as this will directly impact the success of AI tools. When doing so, it is important to understand the crucial role of data integrity – and by extension, data enrichment – in powering these innovative systems, and how real-world applications can help make AI actionable. One form of AI revolutionising the way in which business leaders source information, create new products, develop new content, and respond in real-time to emerging events, is generative AI. Generative AI drives transformation, focusing on machines’ ability to generate meaningful and novel creations. Fuelled by powerful machine learning (ML) models known as foundation models (FMs), generative AI taps into vast datasets and patterns to create outputs that mimic or easily retrieve data in a conversational way. The implications of generative AI

are vast, driving organisations of all sizes to explore and leverage FMs to transform their businesses and elevate the value they deliver to customers. The quest to harness the full potential of generative AI relies on finding high-performing FMs and trustworthy data to achieve outstanding results for diverse use cases. With the continued growth and transformative impact of generative AI, business leaders need to ensure that the data being fed into it has integrity. DATA INTEGRITY AND AI Trusting data is the cornerstone of successful AI and ML initiatives, and data integrity is the key that unlocks its full potential. Data integrity means having accurate, consistent, and contextually relevant data – the kind of data business leaders can confidently rely on to make informed decisions and drive their organisation forward. Yet, achieving data integrity is a complex task, and many organisations need help with data challenges that stand in the way.

Data often resides in isolated silos, grows stale over time, lacks standardisation, may be riddled with duplicates, and does not leverage third-party data and spatial insights to add context, diminishing its integrity and reliability. Without data integrity, organisations risk compromising their AI and ML initiatives due to unreliable insights that do not fuel business value, but with it, the rewards are immense. A robust data integrity strategy helps companies to achieve and maintain trusted data, fuelling more dependable AI results, and allowing confident data-driven decisions to be made to help grow the business, stay agile, reduce costs, and manage risk and compliance. Data enrichment is an essential part of the data integrity journey. Enhancing data with additional information, such as points of interest, property attributes, demographics, and risk information, increases the context and relevance of AI models’ outputs. This enrichment process involves various techniques, such as pre-processing, cleaning,

and incorporating contextual embeddings. Fine-tuning large language models on trusted third-party enrichment datasets allows them to learn from domain-specific patterns, making their outputs more accurate and relevant. Human review further ensures the accuracy and relevance of the dataset, addressing potential biases or errors in the training data and preventing misinformation, ethical concerns, security risks, and other negative implications. Ultimately, when organisations thoughtfully leverage data enrichment as part of their overall data integrity strategy, they unlock the full potential of AI models, driving transformative solutions across your various domains. Enhancing customer interactions with generative AI In today’s digital world, the pressure is on to stay competitive, and that means providing the highest levels of customer experience possible. Companies can adapt FMs to generate fast responses to customer queries based on

May 2023

the latest information from their enterprise knowledge repository – resulting in highly accurate chatbots that can provide the right answers to customers quickly and seamlessly. However, large language models (LLMs) have certain limitations. Trained on general domain corpora, they might not be as effective on domain-specific tasks. To be truly accurate, a chatbot needs precise answers based on specific data rather than generic information. This is where retrieval augmented generation (RAG) and fine-tuning techniques come into play. RAG is a game-changer that combines the power of LLMs with external knowledge, while fine-tuning adapts the model to specific datasets, enhancing its performance with domainspecific nuances. By retrieving contextual documents from outside the language model and incorporating them during execution, RAG, complemented by fine-tuning, enhances the model’s performance. PropTech companies, for example, can leverage LLMs with RAG and

fine-tuning to access even richer and more robust information about a property. By simply asking a chatbot a question, they can receive precise and up-to-date responses about property details, neighbourhood safety, and demographics. The integration of RAG and fine-tuning streamlines the process, resulting in the ability to serve customers faster, research property information more efficiently, and ultimately increase sales and profit. This is another instance where data enrichment can be harnessed to enhance the value of data used for generative AI models – and ultimately help produce greater context and relevance in the models’ outputs. Enriching data with additional attributes and variables, like points of interest and demographics, ensures accurate, contextually grounded responses to customer inquiries. Together, data enrichment, RAG, and fine-tuning form a powerful trio that unleashes the full potential of generative AI – and they are also crucial pillars in generative AI’s evolution. As the PropTech

industry, and others, continue to leverage ML solutions, integrating these powerful techniques will revolutionize customer interactions, streamline research processes, and ultimately boost business outcomes. GENERATIVE AI MARKS A SIGNIFICANT PARADIGM SHIFT Generative AI enables machines to produce novel and contextually relevant content. With advancements in ML and the development of powerful generative AI models, there is a tremendous transformation in AI capabilities. However, the true power of generative AI can only be fully realised with data integrity. Trusting the data that feeds these models is crucial for delivering reliable, accurate results that empower organisations to make well-informed, data-driven decisions. Achieving data integrity is no easy feat, but with advancements in techniques, vast and diverse data availability, and cloud computing capabilities. As generative AI continues

to evolve, the role of data integrity, including powerful data enrichment capabilities, and RAG and fine-tuning models will play a pivotal role in unlocking the true potential of AI models across various industries. When organisations embrace these powerful techniques, they elevate their AI initiatives to new heights, delivering trustworthy and dependable results that propel their business toward success.

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