Investigating Sustainable Production Planning of an Industrial Progressive Die Stamping Process Using Discrete Event Simulation

TY - GEN

T1 - Investigating Sustainable Production Planning of an Industrial Progressive Die Stamping Process Using Discrete Event Simulation

AU - Borbolla Muñoz, Adrián

AU - Nezar Aboujarra, Mohamed

AU - Ramanujan, Devarajan

PY - 2024/11/13

Y1 - 2024/11/13

N2 - This paper investigates the use of discrete event simulation (DES) as a potential decision-support tool for environmentally sustainable production planning. We propose a comprehensive methodology that integrates DES design, dynamic CO2 intensity calculations, and in-depth scenario analysis. This approach facilitates simulation-driven production planning with an emphasis on evaluating and reducing the environmental impacts of manufacturing. Our methodology is applied to the evaluation of an industrial progressive die stamping process (PDSP). The PDSP is a part of a production line in a large Danish manufacturing company. The performance of the PDSP was simulated and evaluated for two working days: 09 Jan 2024 and 10 Jan 2024. Key performance indicators like utilization rate and lead time are assessed alongside environmental sustainability metrics such as process CO2 emissions and CO2 emissions per product. Building upon this baseline, we then simulate and compare two alternative production scenarios: i) increased production capacity and ii) variations in planning orders. These scenarios are then contrasted with the baseline model. Our results demonstrate the potential of DES in identifying new production strategies. The first scenario demonstrates a 7% increase in production capacity, corresponding to a 2.6% increase in process CO2 emissions. The second scenario demonstrates a 5% reduction in process CO2 emissions while retaining the same production capacity as the baseline model. These findings illustrate how DES can uncover production plans that prioritize sustainable manufacturing.

AB - This paper investigates the use of discrete event simulation (DES) as a potential decision-support tool for environmentally sustainable production planning. We propose a comprehensive methodology that integrates DES design, dynamic CO2 intensity calculations, and in-depth scenario analysis. This approach facilitates simulation-driven production planning with an emphasis on evaluating and reducing the environmental impacts of manufacturing. Our methodology is applied to the evaluation of an industrial progressive die stamping process (PDSP). The PDSP is a part of a production line in a large Danish manufacturing company. The performance of the PDSP was simulated and evaluated for two working days: 09 Jan 2024 and 10 Jan 2024. Key performance indicators like utilization rate and lead time are assessed alongside environmental sustainability metrics such as process CO2 emissions and CO2 emissions per product. Building upon this baseline, we then simulate and compare two alternative production scenarios: i) increased production capacity and ii) variations in planning orders. These scenarios are then contrasted with the baseline model. Our results demonstrate the potential of DES in identifying new production strategies. The first scenario demonstrates a 7% increase in production capacity, corresponding to a 2.6% increase in process CO2 emissions. The second scenario demonstrates a 5% reduction in process CO2 emissions while retaining the same production capacity as the baseline model. These findings illustrate how DES can uncover production plans that prioritize sustainable manufacturing.

KW - Discrete Event Simulation

KW - Progressive Die Stamping

KW - Sustainable Manufacturing

UR - http://www.scopus.com/inward/record.url?scp=85210564980&partnerID=8YFLogxK

U2 - 10.1115/DETC2024-143648

DO - 10.1115/DETC2024-143648

M3 - Article in proceedings

VL - 5

BT - 29th Design for Manufacturing and the Life Cycle Conference (DFMLC)

PB - American Society of Mechanical Engineers (ASME)

T2 - ASME 2024 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference

Y2 - 25 August 2024 through 28 August 2024

ER -