A support vector machine model for due date assignment in manufacturing operations

Dalalah, Doraid and Ojiako, Udechukwu and Alkhaledi, Khaled A. and Marshall, Alasdair (2023) A support vector machine model for due date assignment in manufacturing operations. Journal of Industrial and Production Engineering, 40 (1). pp. 68-85. ISSN 2168-1023 (https://doi.org/10.1080/21681015.2022.2059791)

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Abstract

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.

  • Item type:Article
    ID code:87957
    Dates:
    Date
    Event
    2 January 2023
    Published
    8 April 2022
    Published Online
    20 March 2022
    Accepted
    15 June 2020
    Submitted
    Notes: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
    Subjects:Technology > Manufactures
    Department:Faculty of Engineering > Design, Manufacture and Engineering Management
    Depositing user: Pure Administrator
    Date deposited:29 Jan 2024 12:21
    Last modified:01 May 2024 01:29
    URI:https://strathprints.strath.ac.uk/id/eprint/87957
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