Sharing Quality‐Distribution Information for the Selective Assembly of Intermediary Components in the Automotive Industry

Abstract

T his study investigates the value of a supplier sharing information about the quality-distribution (i.e., dimensional mean or variance) of components with an assembler who matches such parts with the selective assembly of an intermediary component. Selective assembly is a strategy that is widely used by high-precision manufacturing companies to gain a competitive advantage in product quality. The use of inexpensive intermediary components (e.g., bearings) to ensure that all mating components are matched with acceptable clearance is a contemporary way of reducing shortage and surplus component costs associated with the traditional fixed-bin selective assembly process. We develop and analyze a Bayesian model for information sharing in this environment, with results indicating that substantial savings occur with the use of shared information from the supplier in a fixed-bin selective assembly of an intermediary-component (FBSAI) context. However, there is a hierarchy regarding benefits, whereas the sharing of information which includes the process mean is most beneficial, and the sharing of only process variance information is least beneficial. The savings can assist the assembler in determining the investment required to create and maintain a profitable quality-distribution information-sharing network of suppliers, thus making the shared information advantageous for both the buying and selling organization.

On Sharing Part Dimensions Information and Its Impact on Design Tolerances In Fixed‐Bin Selective Assembly

“…Information about both and values was more valuable for FBSA than information about only , which in turn was more valuable than information about only . Clottey and Benton (2020) obtained a similar result in a different selective assembly context, when the focus was safety‐stock reduction due to shared information. The current study indicates that this result also applies to FBSA with matchable degree as a criterion.…”

“…To determine the benefit of receiving information about , , or both from the RB supplier, we adopted a Bayesian lens. A Bayesian approach to evaluating the impact of shared information has a firm grounding in statistical decision theory (Raiffa and Schlaifer 1959) and has likewise been employed in other studies (Clottey and Benton 2020, Eppen and Iyer, 1997, Milner and Kouvelis 2002) involving the effect of shared information on predicted quantities. In this study, we want to evaluate the impact of shared information, vs. using just historical data, to estimate the mean and/or variance of incoming part dimensions.…”

“…Additionally, we found that such information becomes more valuable for reducing mismatches if existing tolerances are loosened. While Clottey and Benton (2020) employed a more reactive approach by adapting safety-stock to manage quality in a selective assembly context, the current approach can be described as a proactive one in which information sharing and design techniques are used instead.…”

“…Examples of its application include the assembly of ball bearings and joints (Shin et al. 2009, Thesen and Jantayavichit 1999), production of pistons and cylinders (Pugh 1986), production of thermometers (Tan and Wu 2012), and prevalent use in the assembly of engines (Caputo and Di Salvo 2019, Clottey and Benton 2020, Wang et al. 2018).…”

Secondhand product quality disclosure strategy of the retailer under different supply chain structures

“…An extensive review of this stream of literature can be found in Guan and Chen (2015). Arya et al (2014), Clottey andBenton (2020), andGuan et al (2020) also consider the disclosure and sharing of quality information. Kuksov and Lin (2010) develop a game-theoretic model and examine the interaction of information provision, product quality, and pricing decisions by competitive firms.…”