7 minute read
Automation at the Industrial IoT edge
INNOVATIONS
Advertisement
NEW PRODUCTS FOR ENGINEERS 52 | Unmanaged Ethernet switch, End-of-arm-tool robot, Temperature controller series, Remote access alarm dialer, External digital sensor links for ultrasonic flow system, Cybersecurity compliance management software, Overspeed detection system, Integrated servo motors See more New Products for Engineers at www.controleng.com/NPE.
BACK TO BASICS 54 | Safety: Learning to think the right way
NEWSLETTER: Machine Control
• Which IEC 61131-3 Programming Language is best? Part 2 • Cost-effective position control boosts stepper motor performance • Researchers giving robots human-like perception of their physical environments • Lidar advances could improve safety, security for vehicles, smartphones • Robotic software improves robot health Keep up with emerging trends: subscribe. www.controleng.com/newsletters.
CFE EDU: Courses on motors, drives; more on the way
Register for the course, “Introduction to Motors and Drives,” to learn how motor sizing impacts efficiency and maintenance, understand motor repair processes, review repair best practices to maintain and improve efficiency, and more. See other motor courses in Virtual Training Day. Watch for Virtual Training Week in October! Learn more at www.controleng.com/online-courses
Control Engineering eBook series: IIoT Cloud Fall Edition
Learn how the Industrial Internet of Things (IIoT) and the cloud are changing manufacturing. This helpful eBook includes articles on introducing analytics into industrial environments, data flow, IIoT sensors and more. Learn more and register to download: www.controleng.com/ebooks/.
Oil & Gas Engineering August issue
Oil & Gas Engineering helps maximize uptime and increase productivity through the use of industry best practices and new innovations, increase efficiency from the wellhead to the refinery by implementing automation and monitoring strategies, and maintain and improve safety for workers and the work environment. Read the digital edition at www.oilandgaseng.com.
controleng.com provides new, relevant automation, controls, and instrumentation content daily, access to databases for new products and system integrators, and online training.
Antti Karjaluoto, Arto Peltomaa, Risto Lehtinen, Dimecc Ltd., an Industrial Internet Consortium (IIC) memberAntti Karjaluoto,
Bridging the AI skills gap for machine manufacturers
More knowledge is needed for use of artificial intelligence (AI) for machine learning (ML) applications. See four ways to improve artificial intelligence, machine learning education.
M
More
Artificial intelligence (AI) talent is difficult to find; few industrial companies have enough in-house AI talent. AI will transform many jobs, and companies should give every employee the knowledge they need to adapt to new AI-enhanced roles. AI resources help implement new business models and better services. User acceptance is required. During the last decade, AI design, development and implementation has expanded in many sectors. Organizations are struggling with AI business potential understanding and with finding AI talent. A growing number of countries have recognized the opportunities provided by artificial intelligence and have prepared a national artificial intelligence strategy. In 2017, Finland was among the first countries to launch an artificial intelligence program. The objective of the program was to make Fin-
INSIGHTS land a leader in the application of artificial intelligence. KEYWORDS: Artificial The Finnish Artificial Intelligence Prointelligence, machine gramme identified a small portion of compalearning nies as forerunners in AI implementation; a An AI skills gap exists for majority of companies are at the early stages of ML applications. using data and AI in operations.For Industry 4.0, more AI and ML knowledge is needed. How to address the AI skills gap Education needs to change A way to address the AI skills gap is to to help AI and ML. increase resources for digital, math and techniCONSIDER THIS Attracting the next generation to manufacturing cal education in general. In addition, the current education system in Finland does not yet pay enough attention to applying AI in differrequires advancing policies ent fields. Academic and training programs are and procedures on AI for ML. unable to keep up with the rapid pace of innoONLINE vation with AI. AI education should start early From the digital edition, click and take place for every education stage. Acaon the headline for more demia, companies and public sector officials details, including footnotes. must work together and ensure comprehenwww.controleng.com/ sive AI curriculums will be available. Masmagazine sive open online courses (MOOCs) show the IIC Journal of Innovation at www.iiconsortium.org has more articles and past editions. way and are a good example of a modern way to educate masses with basic AI knowledge. However, deeper understanding often requires www.controleng.com/ tailored education modules. webcasts The manufacturing sector is currently lagging behind in AI and ML use compared to many other industries. Adopting new technologies, especially in process industries, requires pedantic planning, which is time consuming. Companies have long histories in optimizing production, and as the life span of investments can last for decades, changes cannot be made rapidly. In addition, the safety and environmental regulations require strict governance.
Drawing from the sector estimates of the PwC AI impact index, PwC [formerly known as PricewaterhouseCoopers, a professional services firm] estimates that by 2023, individual industry sectors may increase operating margins (how much of each euro of revenues is left over after both costs of goods sold and operating expenses are considered) by 60 to 100%. The difference in the industry specific “AI boost curve” shapes reflect the impact of two factors: 1) the speed the industries are capable of adopting different AI applications and 2) the AI solution development to address the industry-specific business issues.
AI manufacturing benefits, barriers
In manufacturing, short-term benefits are expected to mostly come from process automation and productivity-based solutions. In the mid-term, more complex processes can be automated as intelligent automation offers considerable potential, and predictive maintenance and optimization applications further boost performance.
Productivity gains from AI and ML are not only dependent on the introduction of the technology itself. There also is a need to change the organization of work and increase employees’ knowledge.
Research shows the biggest barrier to AI and machine learning adoption is the skills gap. Most of the time, surveys refer to the technical skills needed to develop AI and ML solutions. However, the biggest skill gap in AI and ML spans the organization.
The Finnish Artificial Intelligence Programme end report pointed out that based on its survey, Finland has high quality education for those aiming to be AI professionals (information technology, mathematics), but there is a gap in the AI applier field. In these fields, the effects of AI would be seen fastest. The working group stated that to achieve the ambitious AI targets,
Epicor® Cloud ERP for Manufacturing
X See your data anytime, anywhere X Collaborate virtually with staff using in-app messaging and ERP data X Improve manufacturing productivity and efficiency
Whether at the shop floor or working virtually, Epicor Software equips businesses with enterprise solutions that shape the exceptional. Realize yours today with manufacturing solutions that give you visibility, collaboration and efficiency.
Contact us today info@epicor.com www.epicor.com
—Krysten Westrum, TEAM Industries
The contents of this document are for informational purposes only and are subject to change without notice. Epicor Software Corporation makes no guarantee, representations, or warranties with regard to the enclosed information and specifically disclaims, to the full extent of the law, any applicable implied warranties, such as fitness for a particular purpose, merchantability, satisfactory quality, or reasonable skill and care. The results represented in this testimonial may be unique to the particular customer as each user’s experience will vary. This document and its contents, including the viewpoints, testimonials, dates, and functional content expressed herein are believed to be accurate as of its date of publication, May 5, 2020. Use of Epicor products and services are subject to a master customer or similar agreement. Usage of the solution(s) described in this document with other Epicor software or third-party products may require the purchase of licenses for such other products. Epicor, and the Epicor logo are trademarks or registered trademarks of Epicor Software Corporation in the United States, and in certain other countries and/or the EU. Copyright © 2020 Epicor Software Corporation. All rights reserved.
