Two stages optimization model on make or buy analysis and quality improvement considering learning and forgetting curve

Abstract

Purpose: The aim of this research is to develop a two stages optimization model on make or buy analysis and quality improvement considering learning and forgetting curve. The first stage model is developed to determine the optimal selection of process/suppliers and the component allocation to those corresponding process/suppliers. The second stage model deals with quality improvement efforts to determine the optimal investment to maximize Return on Investment (ROI) by taking into consideration the learning and forgetting curve.

Design/methodology/approach: The research used system modeling approach by mathematically modeling the system consists of a manufacturer with multi suppliers where the manufacturer tries to determine the best combination of their own processes and suppliers to minimize certain costs and provides funding for quality improvement efforts for their own processes and suppliers sides.

Findings: This research provides better decisions in make or buy analysis and to improve the components by quality investment considering learning and forgetting curve.

Research limitations/implications: This research has limitations concerning investment fund that assumed to be provided by the manufacturer which in the real system the fund may be provided by the suppliers. In this model we also does not differentiate two types of learning, namely autonomous and induced learning.

Practical implications: This model can be used by a manufacturer to gain deeper insight in making decisions concerning process/suppliers selection along with component allocation and how to improve the component by investment allocation to maximize ROI.  

Originality/value: This paper combines two models, which in previous research the models are discussed separately. The inclusions of learning and forgetting also gives a new perspective in quality investment decision.