TY - JOUR
T1 - Improvement of demand fulfillment in Advanced Planning System through decentralized decision support system
AU - Mousavi, Behrouz Alizadeh
AU - Heavey, Cathal
AU - Millauer, Chirine
AU - Tian, Zhikang
AU - Ehm, Hans
N1 - Publisher Copyright:
© 2023
PY - 2023/10
Y1 - 2023/10
N2 - In a tight supply situation, industries such as the semiconductor sector face challenges in allocating supply to customers through complex hierarchical supply chain planning systems, which involve the use of Advanced Planning Systems (APS) and human planners in updating allocation plans. This article focuses on designing, developing, and testing a prototype Decision Support System (DSS) based on a mathematical model to assist human planners and improve demand fulfillment systems in APS when demand exceeds supply. By incorporating digitalization and supporting human interventions in planning, our approach enhances these systems. The bi-objective mathematical model aims to maximize customer service levels while maintaining a maximum amount of stock available for unforeseen planning situations. We developed the proposed mathematical model into a web application decision support tool, called the Regional Customer Allocation Support Tool (ReCAST). The ReCAST prototype was applied to a semiconductor case study, demonstrating its effectiveness in supporting decision-making processes by planners in a real-world context.
AB - In a tight supply situation, industries such as the semiconductor sector face challenges in allocating supply to customers through complex hierarchical supply chain planning systems, which involve the use of Advanced Planning Systems (APS) and human planners in updating allocation plans. This article focuses on designing, developing, and testing a prototype Decision Support System (DSS) based on a mathematical model to assist human planners and improve demand fulfillment systems in APS when demand exceeds supply. By incorporating digitalization and supporting human interventions in planning, our approach enhances these systems. The bi-objective mathematical model aims to maximize customer service levels while maintaining a maximum amount of stock available for unforeseen planning situations. We developed the proposed mathematical model into a web application decision support tool, called the Regional Customer Allocation Support Tool (ReCAST). The ReCAST prototype was applied to a semiconductor case study, demonstrating its effectiveness in supporting decision-making processes by planners in a real-world context.
KW - Advanced Planning System
KW - Customer Allocation
KW - Decision support tool
KW - Mixed-integer programming
KW - Supply chain planning
UR - http://www.scopus.com/inward/record.url?scp=85163885524&partnerID=8YFLogxK
U2 - 10.1016/j.jii.2023.100487
DO - 10.1016/j.jii.2023.100487
M3 - Article
AN - SCOPUS:85163885524
SN - 2452-414X
VL - 35
JO - Journal of Industrial Information Integration
JF - Journal of Industrial Information Integration
M1 - 100487
ER -