Abstract
The integration of scheduling and process planning can eliminate resource conflicts and hence improve the performance of a manufacturing system. However, the focus of most existing works is mainly on the optimization techniques to improve the makespan criterion instead of more efficient uses of energy. In fact, with a deteriorating global climate caused by massive coal-fired power consumption, carbon emission reduction in the manufacturing sector is becoming increasingly imperative. To ease the environmental burden caused by energy consumption, e.g., coal-fired power consumption in use of machine tools, this research considers both makespan as well as environmental performance criteria, e.g., total power consumption, in integrated process planning and scheduling using a novel multi-objective memetic algorithm to facilitate a potential amount of energy savings; this can be realized through a better use of resources with more efficient scheduling schemes. A mixed-integer linear programming (MILP) model based on the network graph is formulated with both makespan as well as total power consumption criteria. Due to the complexity of the problem, a multi-objective memetic algorithm with variable neighborhood search (VNS) technique is then developed for this problem. The Kim’s benchmark instances are employed to test the proposed algorithm. Moreover, the TOPSIS decision method is used to determine the most satisfactory non-dominated solution. Several scenarios are considered to simulate different machine automation levels and different machine workload levels. Computational results show that the proposed algorithm can strike a balance between the makespan criterion and the total power consumption criterion, and the total power consumption can be affected by machine tools with different automation levels and different workloads. More importantly, results also show that energy saving can be realized by completing machining as early as possible on a machine tool and taking advantage of machine flexibility.
Highlights
Process planning and scheduling are two important functions in a flexible manufacturing system (FMS) [1,2,3]
According to existing publications [8,9,10,11,12,13,14,15,16], corresponding research on integrated process planning and scheduling (IPPS) are quite fruitful, and significant improvements have been achieved with the objective of makespan minimization, which is a primary criterion to evaluate the effectiveness of a schedule scheme
For the idle energy consumption, marked in cyan color, there is no apparent fluctuation since the idle energy consumption takes a relative fixed percentage in each instance; more importantly, machines are not allowed to be turned off in this research unless all the operations are finished and this is the other reason there is no significant differences between idle energy consumptions of the instances in Figure 10a. since each machine has only two status—in machining state or in idle state—and all the 15 machines are used in all the three instances, the idle power consumption of machines can be deemed as a constant
Summary
Process planning and scheduling are two important functions in a flexible manufacturing system (FMS) [1,2,3]. In contrast to process planning, scheduling relates more closely to shop floor activities; it allocates operations to one of the available machines from another perspective, e.g., makespan minimization [2] These two functions are treated separately and sequentially [6,7,8,9], and the critical failing is that this will cause resource conflicts in the shop. A previously determined process plan may not be used in actual manufacturing procedure due to some bottleneck machines on shop floor because the real-life shop floor status has not been considered in generating the process plan Such resource conflicts greatly restrict the flexibility in a FMS. The proposed symbiotic evolutionary algorithm lacks effective local search methods
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