Make or buy analysis model based on tolerance allocation to minimize manufacturing cost and fuzzy quality loss

2nd International Manufacturing Engineering Conference; 3rd Asia-Pacific Conference on Manufacturing Systems

Rosyidi, C.N.^1 ; Puspitoingrum, W.^1 ; Jauhari, W.A.^1 ; Suhardi, B.^1 ; Hamada, K.^2

Department of Industrial Engineering, Sebelas Maret University, Surakarta, Indonesia^1

Hiroshima University, Hiroshima, Japan^2

关键词: Manufacturing cost;    Meta-heuristic approach;    Optimization modeling;    Process capabilities;    Production capacity;    Quality of product;    Supplier selection;    Tolerance allocation;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/114/1/012082/pdf
DOI  :  10.1088/1757-899X/114/1/012082

来源: IOP

【 摘 要 】

The specification of tolerances has a significant impact on the quality of product and final production cost. The company should carefully pay attention to the component or product tolerance so they can produce a good quality product at the lowest cost. Tolerance allocation has been widely used to solve problem in selecting particular process or supplier. But before merely getting into the selection process, the company must first make a plan to analyse whether the component must be made in house (make), to be purchased from a supplier (buy), or used the combination of both. This paper discusses an optimization model of process and supplier selection in order to minimize the manufacturing costs and the fuzzy quality loss. This model can also be used to determine the allocation of components to the selected processes or suppliers. Tolerance, process capability and production capacity are three important constraints that affect the decision. Fuzzy quality loss function is used in this paper to describe the semantic of the quality, in which the product quality level is divided into several grades. The implementation of the proposed model has been demonstrated by solving a numerical example problem that used a simple assembly product which consists of three components. The metaheuristic approach were implemented to OptQuest software from Oracle Crystal Ball in order to obtain the optimal solution of the numerical example.