TY - JOUR
T1 - The Impact of Partial Production Capacity Sharing via Production as a Service
AU - Liepold, Christina J.
AU - Arslan, Okan
AU - Laporte, Gilbert
AU - Schiffer, Maximilian
N1 - Publisher Copyright:
© 2024 The Authors
PY - 2024/5
Y1 - 2024/5
N2 - Cloud manufacturing, one of the trends subsumed under Industry 4.0, influences industrial production settings as it transforms resource utilization into a shared on-demand service. Central to cloud manufacturing is the Production as a Service (PaaS) paradigm, which allows intermediaries to coordinate supply and demand of idle production capacities and enables collaboration in production through outsourcing. Current practical implementations of PaaS use multiple steps to connect buyers and suppliers through an intermediary that treats each demand request individually and subsequently contacts a pool of suppliers. In contrast, we study a novel optimization-based PaaS approach and develop a combinatorial exchange model for production capacity sharing among multiple suppliers and buyers. To this end, we adapt the winner determination problem from procurement auction settings. We find that key performance indicators such as matched capacity, overall payment, and unfulfilled minimum demand depend on both the employed bidding behavior and the buyer and supplier ratio. We additionally develop a corresponding online counterpart that can be readily implemented in practice and show that it yields close to optimal solutions. Finally, we show that our solution approach increases the efficiency of matching idle production capacities on average by 39% and also increases the average supplier payoff by up to 74% compared to a practice-based benchmark heuristic.
AB - Cloud manufacturing, one of the trends subsumed under Industry 4.0, influences industrial production settings as it transforms resource utilization into a shared on-demand service. Central to cloud manufacturing is the Production as a Service (PaaS) paradigm, which allows intermediaries to coordinate supply and demand of idle production capacities and enables collaboration in production through outsourcing. Current practical implementations of PaaS use multiple steps to connect buyers and suppliers through an intermediary that treats each demand request individually and subsequently contacts a pool of suppliers. In contrast, we study a novel optimization-based PaaS approach and develop a combinatorial exchange model for production capacity sharing among multiple suppliers and buyers. To this end, we adapt the winner determination problem from procurement auction settings. We find that key performance indicators such as matched capacity, overall payment, and unfulfilled minimum demand depend on both the employed bidding behavior and the buyer and supplier ratio. We additionally develop a corresponding online counterpart that can be readily implemented in practice and show that it yields close to optimal solutions. Finally, we show that our solution approach increases the efficiency of matching idle production capacities on average by 39% and also increases the average supplier payoff by up to 74% compared to a practice-based benchmark heuristic.
KW - Production as a Service
KW - Servitization
KW - Sharing platforms
KW - Winner determination problem
UR - http://www.scopus.com/inward/record.url?scp=85185829148&partnerID=8YFLogxK
U2 - 10.1016/j.cor.2024.106587
DO - 10.1016/j.cor.2024.106587
M3 - Article
AN - SCOPUS:85185829148
SN - 0305-0548
VL - 165
JO - Computers and Operations Research
JF - Computers and Operations Research
M1 - 106587
ER -