Topic(s)
- Operations improvement
Overview
When looking at market research reports and the news, one might assume that every manufacturer in the U.S. is deploying AI on their shop floors. While there is a lot of interest, the reality is more nuanced: adoption of AI-based solutions in manufacturing is still fairly slow as companies try to figure out how to best go about it. Challenges related to data availability and quality, as well as technology, are real. However, the main issue is often change management. Manufacturing leaders are uncertain how to make this new technology work for and with their existing personnel and how to avoid creating a dependency on an AI supplier. This discussion will focus on real-life experience developing and implementing such solutions in manufacturing environments and offer examples to illustrate the learning objectives in a relevant context.
Key learning objectives
- Learn how manufacturers can and should utilize existing expertise deploying AI-based solutions on the shopfloor
- Learn how manufacturers can build new AI-relevant capabilities in-house to future-proof their manufacturing operations
- Learn how manufacturers gain a sustainable competitive advantage by developing these critical capabilities in-house instead of outsourcing them to an external supplier. Building AI-capabilities in house based on an AI platform purpose-built for manufacturing does not only allow existing personnel to continue to do high-value work; it also facilitates hiring, builds critical expertise in-house and keeps the cost of the solution down.
Companies
Autoliv, Inc. (NYSE: ALV; Nasdaq Stockholm: ALIV.sdb) is the worldwide leader in automotive safety systems. Through its group companies, it develops, manufactures and markets protective systems, such as airbags, seatbelts and steering wheels, for all major automotive manufacturers in the world. It also offers mobility safety solutions, such as pedestrian protection, connected safety services and safety solutions for riders of powered two-wheelers. Autoliv challenges and redefines the standards of mobility safety to sustainably deliver leading solutions. In 2023, its products saved 35,000 lives and reduced more than 450,000 injuries. The company’s 70,000 associates in 25 countries are passionate about their vision of Saving More Lives. Quality is at the heart of everything they do. The company drives innovation, research and development at its 14 technical centers with 20 test tracks. Sales in 2023 amounted to $10.5 billion. https://www.autoliv.com/
Founded in 2019, Accella AI provides cutting-edge AI-enabled solutions for manufacturing companies that allow them to reduce cost, improve quality and better utilize existing personnel and equipment. The Accella AI Bot platform enables companies to implement state-of-the-art AI-based solutions for quality control, predictive maintenance and analytics, and human-machine interface (HMI) simplification quickly, and with existing personnel. Accella AI’s solution lowers the barrier to AI adoption and shields companies from the complexities of model development and life cycle management. www.accella.ai
Presenters
Niran Audimoolam is vice president for quality at Autoliv America. He’s been in automotive manufacturing for over 30 years and has vast experience working with OEM and Tier 1 suppliers globally. He brings expertise in integrating quality assurance and management practices from end to end in the value chain with an emphasis on predicting and preventing errors incremental to standard defect detection approaches. Audimoolam has a passion for driving technology-based solutions critical to behavior attributes that push rapid and sustainable transformations. 
Uli Palli is an AI expert and IT professional with 25 years of experience in the high-tech and consumer product industries. His core competency is building solutions for manufacturing customers that leverage technology as their key competitive advantage to drive revenue and reduce cost.
His clients include companies like 3Com, Agilent, Cisco, Chegg, Duracell, eBay, Gestamp, Levi Strauss, HP, NetApp, Siemens, Superior Industries, Synopsys, Xilinx and several Silicon Valley high-tech startups. His experience includes:
- Designing and implementing AI solutions for manufacturing companies with focus on visual quality control and predictive maintenance
- Driving the implementation of data analysis platforms and using Machine Learning for advanced analytics
- Developing AI roadmaps for manufacturing companies
- Program managing ERP and CRM systems implementations (SAP, Oracle, Salesforce)
- Managing software development teams in Fortune 500 high-tech companies
- Developing technical roadmaps in close collaboration with senior executives and technical teams
Palli holds a B.A. degree in business administration from Karl Franzens University in Graz, Austria and an MBA from Heriot-Watt University in Edinburgh, Scotland. Prior to his career in artificial intelligence, Palli worked as a business consultant for a large U.S. consulting company and as a product manager and key account manager in the software industry.
