TY - JOUR
T1 - Corrected Aggregate Workload approach on order release by considering job’s routing position induced variable indirect load
AU - Yuan, Mingze
AU - Ma, Lin
AU - Qu, Ting
AU - Thürer, Matthias
AU - Huang, George Q.
N1 - Funding information:
This paper is financially supported by the National Key Research and Development Program of China (2021YFB3301701), 2019 Guangdong Special Support Talent Program –
Innovation and Entrepreneurship Leading Team (China) (2019BT02S593), 2018 Guangzhou Leading Innovation Team Program (China) (201909010006), and the Science and Technology Development Fund (Macau SAR) (0078/2021/A). We also appreciate the sponsorships from the industry, including but not limited to Carpoly Chemical Group Co., Ltd. Guangdong International Cooperation Base of Science and Technology for GBA Smart Logistics is a provincial research lab sponsored by the Department of
Science and Technology of Guangdong Province, thanks to which the international collaboration has been effectively conducted
Publisher Copyright:
© 2024, Emerald Publishing Limited.
PY - 2024/12/2
Y1 - 2024/12/2
N2 - Purpose: Workload contribution calculation approaches in the existing literature overestimate or underestimate indirect workload, which increases both workload fluctuation and shop floor throughput performance. This study optimizes a Corrected Aggregate Workload (CAW) approach to control the workload contribution of workstations and Work In Progress (WIP) levels, thereby improving the shop floor throughput performance.Design/methodology/approach: This study adopts simulation experiment by SimPy, and experimental factors are: (1) two workload contribution methods (CAW method and considering Position Corrected Aggregate Workload [PCAW] method); (2) two release methods (LUMS COR release and immediate release); (3) eleven workload norms for LUMS COR release (from 7- to 15-time units), and infinite workload norm for immediate release; and (4) two dispatching rules (First Come First Served, FCFS and Operation Due Date, ODD). Each scenario is replicated 100 times, and for each replication data are collected for 10,000 time units, being the warm-up period set to 3,000-time units. Findings: The results of this study confirm that the PCAW calculation method outperforms the CAW method, especially during higher workload norm levels. The PCAW method is considered the better solution in practice due to its excellent performance in terms of percentage tardiness and mean tardiness time. The efficient workload contribution approach, as discussed in this study, has the potential to offset delivery performance loss that results from throughput performance loss. Originality/value: This study proposes a novel approach that considers the workstations’ position in the routing of the job and the position of jobs CAW method. The results demonstrated that it allows shop floor throughput time to be short and feasible. It controls WIP by workload contribution of workstations, resulting in a lean shop floor. Therefore, workload contribution calculation is of particular significance for high-variety Make-To-Order (MTO) companies.
AB - Purpose: Workload contribution calculation approaches in the existing literature overestimate or underestimate indirect workload, which increases both workload fluctuation and shop floor throughput performance. This study optimizes a Corrected Aggregate Workload (CAW) approach to control the workload contribution of workstations and Work In Progress (WIP) levels, thereby improving the shop floor throughput performance.Design/methodology/approach: This study adopts simulation experiment by SimPy, and experimental factors are: (1) two workload contribution methods (CAW method and considering Position Corrected Aggregate Workload [PCAW] method); (2) two release methods (LUMS COR release and immediate release); (3) eleven workload norms for LUMS COR release (from 7- to 15-time units), and infinite workload norm for immediate release; and (4) two dispatching rules (First Come First Served, FCFS and Operation Due Date, ODD). Each scenario is replicated 100 times, and for each replication data are collected for 10,000 time units, being the warm-up period set to 3,000-time units. Findings: The results of this study confirm that the PCAW calculation method outperforms the CAW method, especially during higher workload norm levels. The PCAW method is considered the better solution in practice due to its excellent performance in terms of percentage tardiness and mean tardiness time. The efficient workload contribution approach, as discussed in this study, has the potential to offset delivery performance loss that results from throughput performance loss. Originality/value: This study proposes a novel approach that considers the workstations’ position in the routing of the job and the position of jobs CAW method. The results demonstrated that it allows shop floor throughput time to be short and feasible. It controls WIP by workload contribution of workstations, resulting in a lean shop floor. Therefore, workload contribution calculation is of particular significance for high-variety Make-To-Order (MTO) companies.
KW - Corrected Aggregate Workload
KW - Indirect workload
KW - Order release
KW - Workload Control
UR - https://www.scopus.com/pages/publications/85193983908
U2 - 10.1108/IMDS-08-2023-0598
DO - 10.1108/IMDS-08-2023-0598
M3 - Journal article
AN - SCOPUS:85193983908
SN - 0263-5577
VL - 124
SP - 2992
EP - 3011
JO - Industrial Management and Data Systems
JF - Industrial Management and Data Systems
IS - 11
ER -