Pharma Research Solutions

Algorithms Recognize the Causes of Errors in the Manufacturing System and Learn from Them

Algorithms Recognize the Causes of Errors in the Manufacturing System and Learn from Them

Fraunhofer researchers have developed an analysis tool that detects faults in fast-cycle production systems and improves troubleshooting

SwissCognitiveThe software has already proven itself in various applications. The pharmaceutical and consumer goods industries, run capital-intensive manufacturing facilities and rely on continuously maximizing productivity. Otherwise there is a risk of cost pressure and financing gaps. However, in practice: “The more complex the plant, the lower the productivity.” This is how Felix Müller, Group Leader Autonomous Production Optimization at Fraunhofer IPA, sums it up. Furthermore, many production plants comprise a large number of stations and process jobs so quickly that the causes of faults cannot be seen with the naked eye.

Using “Smart System Optimization”, Müller and his team have developed an analysis tool that continuously detects errors and their causes in fast-acting, interlinked production systems: A powerful connector accesses the data in the machine control system at high frequency via the respective manufacturer protocol. The result is a continuous database, which is evaluated by several self-learning algorithms synchronously. They identify where faults during production arise, how they are related and what their priorities are in relieving them. In this way, defects that lead to the failure of the entire system can be repaired or even predicted more quickly.

Operator Assistance System Continuously Learns New Things

However, it is not always clear what to do if an error is going to occur. Additionally, follow-up messages from the system make the situation even more confusing for the operator. For this reason, Müller and his team have developed Shannon, an intelligent operator assistance system for complex production lines based on “Smart System Optimization”. Until now, it was often up to the machine operators to decide what to do to correct a fault. Now, however, the affected machine sends them a detailed step-by-step guide to the smartphone or tablet. The database and the links between faults and solutions are constantly being expanded during plant operation.

This gives system operators the opportunity to create their own instructions, for example on troubleshooting measures. These instructions can include text, photos or videos. Furthermore, the plant operator can give feedback on the information provided, which is used to improve it. Plant operators are also actively encouraged to contribute knowledge, for example in the description of detected but unknown events. In this way a clearly understandable and continuously linked knowledge base comprising errors, events and solutions can be established. Shannon is currently used as a tablet and smartphone app in several factories, where it has significantly reduced the time it takes to troubleshoot problems.[…]

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Photo: From scientists to company founders (from left): Thomas Hilzbrich, Pablo Mayer and Felix Müller have developed the “Smart System Optimization”. Now the scientists are starting their own business based on this technology. ( Source: Fraunhofer IPA / Photo: Rainer Bez )

1 Comment

  1. Corey👨🏻‍💻📲📈💵

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