The conceptual framework of production planning optimisation using fuzzy inference system with Tsukamoto
In today’s dynamic environment, activities in manufacturing have become uncertain and complex. This is because there is always ambiguity in different states due to their diversity. In other words, the uncertainty can make the operations in the manufacturing companies become finite and result in unne...
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| Format: | Article |
| Published: |
Universiti Malaysia Pahang
2016
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| Online Access: | http://eprints.uthm.edu.my/8594/ |
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| Summary: | In today’s dynamic environment, activities in manufacturing have become uncertain and
complex. This is because there is always ambiguity in different states due to their diversity.
In other words, the uncertainty can make the operations in the manufacturing companies
become finite and result in unnecessary waste of resources in terms of money, labour or time.
Therefore, production and inventory planning are essential activities to accurately predict
production in the manufacturing sector. In the context of such factors, the purpose of this
research is to introduce the Fuzzy Inference System (FIS) as an effective method that can
assist in determining an optimal result to each fuzzy variable. The fuzzy variables of
customer demand, production and inventory are used to practice the theory, synthesizing the
activities in manufacturing in order to attain an effective and efficient operation in the
industry. Specifically, electrical and electronics-related manufacturing companies are the
engine of growth in Malaysia; therefore, FIS with Tsukamoto is implemented to facilitate and
accelerate the decision-making processes within the company. In general, it is a simple
method that can help to determine the optimal and appropriate quantity of manufactured
goods to be handled within the operation by using the variables in the form of fuzzy numbers. |
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