An extensive evaluation of CONWIP-card controlled and scheduled start time based production system designs. (January 2019)

• Record Type: Journal Article
• Authors: Roy, Debjit; Ravikumaran, Vasudha
• Is Part Of: Journal of manufacturing systems. Volume 50(2019)
• Page Start: 119
• Page End: 134
• Publication Date: 2019-01
• Subjects: Manufacturing system -- Tandem stations -- Order release policies -- Queuing network models -- Throughput matching; Manufacturing processes -- Periodicals; Production engineering -- Data processing -- Periodicals; Robots, Industrial -- Periodicals; Production, Technique de la -- Informatique -- Périodiques; Robots industriels -- Périodiques; Electronic journals; 670.42
• DOI: 10.1016/j.jmsy.2018.12.006
• Languages: English
• ISSNs: 0278-6125

Abstract

Highlights: Compare CONWIP policy (closed system) with open control policies (such as deterministic start times). Develop a throughput matching algorithm to match the throughput of the closed system with an open system. The throughput time percentage benefit using CONWIP in comparison to open control is 1/ K, where K is the number of stations. Abstract: Order release policies such as a card-controlled CONWIP policy aim to improve system responsiveness and minimize system-wide inventory levels. It is not clear if order release policies (without card control) can be equally effective under certain settings of the production system design parameters. In this research, we study the performance of alternate order release (material control policies) such as CONWIP and scheduled start time policy under a variety of design parameter settings such as number of stations, station service time characteristics, availability of raw material, and the location of the bottleneck station using queuing network models. Using an exhaustive numerical study, we observe that throughput times in CONWIP systems are about 2–50% less compared to open control systems; however, for a balanced system, the Deterministic scheduled start time policy performs equally well for a large set of production system designs. We further identify that the number of stations and the location of the bottleneck station affect the choice of the order release policy. Additionally, we also analyze the system for a variety of demand inter-arrival times and check its effect on the expected number of backlogs and system-wide expected waiting times.