AI in manufacturing operations – Lack of internal capabilities will drive the need for external specialists
Artificial intelligence (AI) and machine learning hold a lot of potential for manufacturers to optimize processes on the enterprise level and on the shop-floor level. While in the sales and marketing domain in particular, we see a lot of use cases of how AI can help manufacturers better understand market demand and better target customers with personalized marketing campaigns, AI is kind of a young topic on the shop floor.
Potential areas where AI can be applied to optimize manufacturing operations are production planning, production and warehouse operations, quality control processes, and maintenance and repair operations:
- In production planning, algorithms and machine learning techniques can be used to solve combinatorial optimization problems on the shop floor or to enable continuous resequencing, and smart capacity and resource planning in a factory.
- In production and warehouse operations, sensor-based solutions that leverage algorithms and machine learning techniques as well as IoT technologies can be used for further automation of processes on the shop floor or in the warehouse, or to increase the efficiency of workers.
- In quality control processes, AI can help to detect errors in manufactured products and goods better and faster than human control procedures can with visual and manual inspection.
- In maintenance and repair operations, AI can help to increase customer satisfaction by avoiding unplanned machine downtimes.
On the one hand, we increasingly observe manufacturing companies looking into how AI can help them to increase the efficiency of their manufacturing operations. On the other hand, however, we also see a lack of own skills related to artificial intelligence and machine learning. This will require a closer collaboration with external IT providers that have both the appropriate AI-related know-how and industry-related domain know-how. In particular, start-ups in this domain are interesting as they often develop very industry-oriented solutions.
In the recently published report “AI in Manufacturing Operations” we focus on AI use cases in manufacturing operations as well as project examples. We particularly highlight those use cases that we have been discussing in our numerous conversations with production, logistics, and service managers over the past 12 months and for which we can share project examples. In addition, we also give our view on the current maturity level of AI in manufacturing operations and the major related challenges.