Quality Improvement Along Supply Chain

Didun Peng, Purdue University

Abstract

Product quality is the core competitiveness of a brand, prompting brand-owner continuously to pursue. Learning curve is the tool to improve product quality by variance reduction. At the same time, knowledge depreciation with its negative effects attracts attention. Thus, a comprehensive learning curve is introduced in this dissertation. This research focus to explore the quality improvement along the supply chain. There are three contributions in this dissertation: 1) it provides the supply chain’s optimal distribution of quality improvement to manufacture and its suppliers; 2) it shows the benefit from coordinated quality improvement among the supply chain; 3) it illustrates the benefit from increased demand and decreased cost from quality improvement. Three models are presented consecutively in this dissertation. The first model assists the supply chain to coordinate all suppliers for quality investment. Based on the traditional learning curve, the comprehensive learning model is introduced in order to better understand the knowledge accumulation effect. Autonomous learning, induced learning and their respective knowledge depreciation effects are considered in this model. The product quality is measured from several aspects, and each aspect linearly depends on the component quality. Therefore, suppliers’ quality improvement contribute to the end product quality. The second model further considers each outsourced components have interaction effects. To better understand knowledge forgetting effect, it adopt Weibull distribution to simulate producing disruption. What’s more, it considers the optimal quality investment for the whole producing system and a suboptimal quality investment when there is no coordination in the system (Dyadic Supply Chain). Without coordination, every supplier is trying to save her own quality cost, but the total quality cost is higher than the coordinated system. Thus, incentives are necessary to these suppliers to cooperate in quality improvement. In addition, the second model provides existence proof of the optimal solution. Since the previous models using variance reduction to save cost, it increases demand as well. The third model starts to consider demand increasing and quality saving simultaneously. Similar to model 2, the third model compares the optimal quality efforts under the coordinated system and the sub-optimal quality efforts under un-coordinated system. Generally, the coordinated system is more efficient. With coordination, 1) marginality is eliminated; 2) cost is lower; 3) demand is higher from higher quality. Since supplier invest more with cooperation, incentives is required to all suppliers.

Degree

Ph.D.

Advisors

Tang, Purdue University.

Subject Area

Management

COinS