Optimizing the smoothness of production lines with considerations of structural and dynamic complexities for electronics manufacturing

In an electronics manufacturing environment, it is very common to find many different products with different features, being manufactured in the same production area. They can share same machines, tools and even same operators. There are various objectives to be achieved in a production work floor,...

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Bibliographic Details
Published in2016 IEEE International Conference on Consumer Electronics-China (ICCE-China) pp. 1 - 13
Main Authors Law, Edward K. W., Yung, Winco K. C.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.12.2016
Subjects
Complexity theory
Dynamic Complexity
Entropy
Information Entropy
Line Balancing
Manufacturing systems
Mathematical model
Mixed-Model Work Flow
Schedules
Structural Complexity
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Summary:In an electronics manufacturing environment, it is very common to find many different products with different features, being manufactured in the same production area. They can share same machines, tools and even same operators. There are various objectives to be achieved in a production work floor, balance of work is recognized as a major target as it eliminates resource idling. However, the traditional methods of line balancing have not considered the impact of complexity in both Structural and Dynamic aspects. A manufacturing system is actually quite complex, as the subsystems can have interactions among themselves. Improving the flexibility also complicates the decision process, and hence the occurrence of different events. Quality tools such as Kanban, Just-in-Time are simpler to use, and many of them can be incremental and easy to communicate to other colleagues. However, they suffer from a non-holistic approach and do not give an overall picture of the interactions. We build up and illustrate an optimization framework by: 1. Reviewing the traditional approach in Multi-Model Line Balancing. 2. Use of Matrix Approach to explore the Line Balancing. 3. Analyzing different results with Information Entropy. 4. Discussing the impact on Structural and Dynamic Complexities.
DOI:10.1109/ICCE-China.2016.7849728