TY - JOUR
T1 - A support vector machine model for due date assignment in manufacturing operations
AU - Dalalah, Doraid
AU - Ojiako, Udechukwu
AU - Alkhaledi, Khaled A.
AU - Marshall, Alasdair
N1 - Copyright © 2022 Taylor & Francis. This is an Accepted Manuscript of an article published by Taylor & Francis in the Journal of Industrial and Production Engineering on 8 April 2022, available at http://www.tandfonline.com/10.1080/21681015.2022.2059791
PY - 2023/1/2
Y1 - 2023/1/2
N2 - The relationship between product flow times and manufacturing system status is complex. This limits use of simple analytical functions for job shop manufacturing due date assigning, especially when dealing with orders involving multiple-resource manufacturing systems in receipt of random orders of different process plans. Our approach involves developing a Support Vector Machine classifier to articulate job shop manufacturing due date assigning in heterogeneous manufacturing environments. The emergent model allows not only for the complex relationships between flowtimes and manufacturing system status, but also for the prediction of random order flowtime of manufacturing systems with multiple resources. Our findings also suggest that service levels play a major role in negotiated due dates and eventual customer propensity to place manufacturing orders. In emphasizing negotiated due dates as against exogenous assigned due dates, the study focuses scholarly attention toward the need for participative, open and inclusive due date assignments.
AB - The relationship between product flow times and manufacturing system status is complex. This limits use of simple analytical functions for job shop manufacturing due date assigning, especially when dealing with orders involving multiple-resource manufacturing systems in receipt of random orders of different process plans. Our approach involves developing a Support Vector Machine classifier to articulate job shop manufacturing due date assigning in heterogeneous manufacturing environments. The emergent model allows not only for the complex relationships between flowtimes and manufacturing system status, but also for the prediction of random order flowtime of manufacturing systems with multiple resources. Our findings also suggest that service levels play a major role in negotiated due dates and eventual customer propensity to place manufacturing orders. In emphasizing negotiated due dates as against exogenous assigned due dates, the study focuses scholarly attention toward the need for participative, open and inclusive due date assignments.
KW - due date
KW - flow time
KW - job shop
KW - kernel function
KW - optimization
KW - support vector machine
U2 - 10.1080/21681015.2022.2059791
DO - 10.1080/21681015.2022.2059791
M3 - Article
AN - SCOPUS:85129150627
SN - 2168-1015
VL - 40
SP - 68
EP - 85
JO - Journal of Industrial and Production Engineering
JF - Journal of Industrial and Production Engineering
IS - 1
ER -