Integration of process planning and scheduling in a job shop environment

Kumar, Manish; Rajotia, Sunil

doi:10.1007/s00170-004-2317-y

Cited by 55 publications

(24 citation statements)

References 32 publications

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“…At the beginning of the research on the IPPS problem, process planning and scheduling are integrated in a sequential manner [13]; this paradigm takes no advantage of the flexibilities in both the process planning module and the scheduling module since there are still serious bottlenecks in actual manufacturing activities. After that, relative research tends to integrate the two functions coherently to achieve a superior overall system performance mainly by three means: (1) mathematical modelling and corresponding solutions; (2) meta-heuristic-based approaches, such as genetic algorithm (GA); and (3) other approaches, e.g., agent-based methods [14].…”

Section: Literature Reviewmentioning

confidence: 99%

“…Due to such limitations and shortcomings in applications of FMSs, relative studies on integrated process planning and scheduling have been performed to achieve an efficient use of an FMS. 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 instance, Doh et al [10] adopted the priority dispatch rules to quickly determine a feasible scheduling scheme; nevertheless, this method usually cannot ensure a competitive solution.…”

Section: Introductionmentioning

confidence: 99%

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Realizing Energy Savings in Integrated Process Planning and Scheduling

2019

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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.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Realizing Energy Savings in Integrated Process Planning and Scheduling

2019

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“…If we look at the early works on IPPS problem, we can see the following literature on this problem; Nasr and Elsayed [10], Hutchinson et al [11], Chen and Khoshnevis [12], Zhang and Mallur [1], Brandimarte [13], Morad and Zalzala [14]. After these studies more works are done on IPPS such as: Ming and Mak [15], Tan and Khoshnevis [16], Kim et al [17], Kumar and Rajotia [18], Lim and Zhang [19], Tan and Khoshnevis [20], Kumar and Rajotia [21], Moon et al [22], Guo et al [23], Leung et al [24], Phanden et al [25], Petrovic et al [26], Zhang et al [27], and Zhang and Wong [28]. Scheduling with due date assignment is also popular research topic which is extensively studied in the literature.…”

Section: Literature Surveymentioning

confidence: 99%

Integrated process planning, WSPT scheduling and WSLK due-date assignment using genetic algorithms and evolutionary strategies

Demir

Canpolat

2017

Int. J. Optim. Control, Theor. Appl. (IJOCTA)

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Process planning, scheduling and due-date assignment are three important manufacturing functions in our life. They all try to get local optima and there can be an enormous loss in overall performance value if they are handled separately. That is why they should be handled concurrently. Although integrated process planning and scheduling with due date assignment problem is not addressed much in the literature, there are numerous works on integrated process planning and scheduling and many works on scheduling with due date assignment. Most of the works in the literature assign common due date for the jobs waiting and due dates are determined without taking into account of the weights of the customers. Here process planning function is integrated with weighted shortest processing times (WSPT) scheduling and weighted slack (WSLK) due date assignment. In this study unique due dates are given to each customer and important customers get closer due dates. Integration of these three functions is tested for different levels of integration with genetic algorithms, evolutionary strategies, hybrid genetic algorithms, hybrid evolutionary strategies and random search techniques. Best combinations are found as full integration with genetic search and hybrid genetic search. Integration of these three functions provided substantial improvements in global performance.

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“…They concluded that the proposed method helps in on-line determination and assignment of loads on various machines. Further, Kumar and Rajotia, (2006) presented a scheme for integration model for job-shop. It considered machine capacity and cost while assigning operation to machines.…”

Section: Non-linear Process Planning and Scheduling Approachmentioning

confidence: 99%