Abstract
Additive manufacturing (AM), also known as 3D printing, has been called a disruptive technology as it enables the direct production of physical objects from digital designs and allows private and industrial users to design and produce their own goods enhancing the idea of the rise of the “prosumer”. It has been predicted that, by 2030, a significant number of small and medium enterprises will share industry-specific AM production resources to achieve higher machine utilization. The decision-making on the order acceptance and scheduling (OAS) in AM production, particularly with powder bed fusion (PBF) systems, will play a crucial role in dealing with on-demand production orders. This paper introduces the dynamic OAS problem in on-demand production with PBF systems and aims to provide an approach for manufacturers to make decisions simultaneously on the acceptance and scheduling of dynamic incoming orders to maximize the average profit-per-unit-time during the whole makespan. This problem is strongly NP hard and extremely complicated where multiple interactional subproblems, including bin packing, batch processing, dynamic scheduling, and decision-making, need to be taken into account simultaneously. Therefore, a strategy-based metaheuristic decision-making approach is proposed to solve the problem and the performance of different strategy sets is investigated through a comprehensive experimental study. The experimental results indicated that it is practicable to obtain promising profitability with the proposed metaheuristic approach by applying a properly designed decision-making strategy.
Highlights
Additive manufacturing (AM), known as 3D printing, has been called a disruptive technology as it enables the direct production of physical objects from digital designs and, allows industrial as well as private users to design and produce their own products enhancing the idea of the rise of the “prosumer” [1, 2]
The decision-making on the order acceptance and scheduling (OAS) will play a crucial role when service providers dealing with on-demand production orders from small and medium enterprise are distributed around the world
The problem of dynamic OAS in on-demand production with powder bed fusion (PBF) systems with part orders dynamically arriving in chronological order was introduced and modelled mathematically to maximize the average profit-per-unit-time during the whole makespan of the system
Summary
Additive manufacturing (AM), known as 3D printing, has been called a disruptive technology as it enables the direct production of physical objects from digital designs and, allows industrial as well as private users to design and produce their own products enhancing the idea of the rise of the “prosumer” [1, 2]. This paper considers a dynamic OAS problem in an ondemand production environment where the service provider with multiple AM machines is making decisions on the acceptance of orders placed by customers and scheduling the accepted orders simultaneously, to maximize the average profitper-unit-time obtained during the whole makespan. The dynamic OAS problem in on-demand production with PBF systems is a joint decision on order acceptance and scheduling of batch processing machines. The dynamic OAS problem is defined and mathematically modelled with constraints of orders’ arrival time and due date for the first time Since both OAS and BPP are strong NP hard problems, in regard to the characteristics of production with PBF systems, a strategy-based heuristic decisionmaking approach is proposed for the generation of feasible schedule solutions.
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