Product state based view and machine learning: A suitable approach to increase quality?

Irgens, Christopher; Wuest, Thorsten; Thoben, Klaus‐Dieter

doi:10.3182/20120523-3-ro-2023.00083

Cited by 2 publications

(3 citation statements)

References 7 publications

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“…Furthermore, the own products and the information involved to describe these products during the manufacturing process have to be assessed carefully. The product state based view can offer a valuable concept to structure and quantify the information needs on a process and product level [10,21]. Fig.…”

Section: Requirements and Recommendations For Implementationmentioning

confidence: 99%

“…The product states have descriptive characters and are interdependent to each other. The surrounding information management system (number four), integrates the process (number one) and product (number two/three) information, processes the information if needed [21] and distributes it to the right addressee.…”

Section: Requirements and Recommendations For Implementationmentioning

confidence: 99%

See 1 more Smart Citation

Information Management for Manufacturing SMEs

Wuest¹,

Thoben²

2012

Advances in Production Management Systems. Value Networks: Innovation, Technologies, and Management

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Manufacturing SMEs are the backbone of the prosperous German engineering sector. Known for advanced technology and premium quality, they face a constant need to improve their processes. This is especially true for SMEs involved in collaborative production networks. Within these networks, each partner is required to constantly improve their process and product quality. One possible method to accomplish this, is by improving the information management based on the product state. An elementary requirement for such a system is to understand the SME specific challenges. This paper will provide an overview of special conditions of manufacturing SMEs, derive requirements on product state based information management and provide insights and recommendations of implementing such a system by using practical examples.

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Section: Requirements and Recommendations For Implementationmentioning

confidence: 99%

Section: Requirements and Recommendations For Implementationmentioning

confidence: 99%

Information Management for Manufacturing SMEs

Wuest¹,

Thoben²

2012

Advances in Production Management Systems. Value Networks: Innovation, Technologies, and Management

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show abstract

“…The flow of the physical product is one directional and at each process step value is added to the product and such the product state (number three) changes by definition. In this way, the product's overall progress may be viewed as a set of concatenated 'state vectors', each vector representing one of the product states [14]. The product states have descriptive characteristics and are partly interdependent of each other as are product states over the whole manufacturing process.…”

Section: Fig 1 Product State Change During Manufacturing Processmentioning

confidence: 99%

Analysis of Manufacturing Process Sequences, Using Machine Learning on Intermediate Product States (as Process Proxy Data)

Wuest¹,

Irgens

Thoben³

2013

IFIP Advances in Information and Communication Technology

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Abstract. Quality and efficiency increased in importance over the last years within the manufacturing industry. To stay competitive companies are forced to constantly improve their products and processes. Today's information technology and data analysis tools are promising to further enhance the performance of modern manufacturing. In this paper, at first, the concept of the product state based view in a distributive manufacturing chain is presented, followed by a brief introduction of relations between product states along the chain. After showing that a in detail description based on cause-effect models is not economical viable today, the possibilities of using machine learning on intermediate product states to analyze the process sequence is introduced and discussed. Providing a chance to analyze large amounts of data with high dimensionality and complexity, machine learning tools combined with cluster analysis are perfectly suited for the task at hand within the product state based concept.

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Product state based view and machine learning: A suitable approach to increase quality?

Cited by 2 publications

References 7 publications

Information Management for Manufacturing SMEs

Information Management for Manufacturing SMEs

Analysis of Manufacturing Process Sequences, Using Machine Learning on Intermediate Product States (as Process Proxy Data)

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