Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/25083
Title: Cost-Based Decision Support System: A Dynamic Cost Estimation of Key Performance Indicators in Manufacturing
Authors: Psarommatis, F
Danishvar, M
Mousavi, A
Kiritsis, D
Keywords: cost functions;hard metal;microelectronics;optimization;process planning;sustainable manufacturing;zero defect manufacturing (ZDM)
Issue Date: 7-Jan-2022
Publisher: IEEE
Citation: Psarommatis, F. et al. (2024) 'Cost-Based Decision Support System: A Dynamic Cost Estimation of Key Performance Indicators in Manufacturing', IEEE Transactions on Engineering Management, 71, pp. 702 - 714. doi: 10.1109/TEM.2021.3133619.
Abstract: © Copyright The Authors 2022. An attempt is made to translate five generic key performance indicators (KPIs) into a continuous real-time cost function in a batch order-based manufacturing environment. The challenge of controlling and optimizing resource utilization, production efficiency, product-process quality, environmental impact, and inventory was specified by microelectronics and hard metal composite manufacturers. The motivation is to facilitate decision-making by converting operations management data into dynamic financial cost models. The process of interpreting engineering data of the physical level and operations management level into financial metrics creates a common language between engineers, managers, and financial departments of the company whose common objective is the profitability of the company, each with their own priorities. The proposed method provides a realistic representation of the performance of the system in monetary value. The integration may become an instrument of effective and efficient tactical and strategic collective decision-making. The main outcome is a near real-time formulation and prediction of manufacturing cost with respect to the five KPIs. The resultant cost function is verified according to several production scenarios. The case study demonstrating the proposed cost modeling methodology utilizes real-time and historical information from two different industrial partners in Tungsten metallurgy and electronic circuit manufacturing industries.
URI: https://bura.brunel.ac.uk/handle/2438/25083
DOI: https://doi.org/10.1109/TEM.2021.3133619
ISSN: 0018-9391
Other Identifiers: ORCID iD: Foivos Psarommatis https://orcid.org/0000-0002-2731-8727
ORCID iD: Morad Danishvar https://orcid.org/0000-0002-7939-9098
ORCID iD: Alireza Mousavi https://orcid.org/0000-0003-0360-2712
ORCID iD: Dimitris Kiritsis https://orcid.org/0000-0003-3660-9187
Appears in Collections:Dept of Mechanical and Aerospace Engineering Research Papers
Dept of Civil and Environmental Engineering Research Papers

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