加工车间软件

最新的CAM和车间评估软件包提供特征识别功能和按客户要求编制的宏程序。     

Multicontextual dispatching rules for job shops with dynamic job arrival

The dynamic job shop problem is more challenging than the static job shop problem because dynamic job shops are disrupted by unforeseen events such as job arrivals and machine breakdowns. Each phase of a dynamic job shop problem presents a unique set of circumstances; multicontextual functions can describe the unique characteristics of a dynamic job shop at a specific time. The present work examines 11 basic dispatching rules and 33 composite rules made with multicontextual functions (MCFs) that describe machine idle time (MIT) and job waiting time (JWT). Simple procedures are presented that allow one or both of MIT and JWT to be combined with a single basic dispatching rule. This procedure produced 33 composite dispatching rules; the schedules from all 44 rules for a job shop with dynamic job arrival were compared with regard to make span and mean flow time. One composite rule, most work remaining with MCF₂, produced schedules with the shortest make spans in 21 out of 27 cases; another composite rule, most remaining operations (MRO) with MCF₃, produced schedules with the shortest mean flow times in 27 out of 27 cases. It was possible to combine JWT and MIT usefully only when the relevant dispatching rule did not depend on operation processing time; because MRO did not consider processing time, it benefitted from both JWT and MIT. Clients who demand short mean flow times might benefit from an implementation of MRO with MCF₃.     

Analysis of reactive deadlock-free scheduling in flexible job shops

Reactive scheduling is a procedure followed in production systems to react to unforeseen events that disturb the normal operation of the system. In this paper, a novel operations insertion heuristic is proposed to solve the deadlock-free reactive scheduling problem in flexible job shops, upon the arrival of new jobs. The heuristic utilizes rank matrices (Latin rectangles) to insert new jobs in schedules, while preventing the occurrence of deadlocks or resolving them using the available buffer space (if any). Jobs with alternative processing routes through the system are also considered. The heuristic can be employed to execute two reactive scheduling approaches in a timely efficient manner; to insert the new jobs in the already existing schedule (job insertion) or to reschedule all the jobs in the system (total rescheduling). Using experimental design and analysis of variance (ANOVA), the relative performance of the two approaches is studied and analyzed to provide some measures and guidelines for selecting the appropriate reactive scheduling approach for different problem settings. Three measures of performance are considered in the analysis; efficiency of the revised schedules in terms of the mean flow time, resulting system nervousness, and the required solution time. The results show that, on average, job insertion obtains revised schedules featuring significantly lower system nervousness and slightly higher mean flow time than total rescheduling. However, depending on the system size, number and processing times of the new jobs, and the available flexibility in the system, a trade-off between the two approaches should sometimes be considered.

面向云制造作业车间的机器能力界定方法

针对面向云制造作业车间,研究不同扰动情形下机器保护能力的设置以及参与云服务能力的划分问题。揭示了系统有效产出随机器能力增长变化的规律。提出了能力松弛率和可用调度时间的概念,建立了面向云制造作业车间的机器能力界定模型。设定了不同的非瓶颈能力松弛率和扰动水平,通过对非瓶颈能力的分级利用,得到了非瓶颈松弛率对系统性能的影响曲线。基于聚类算法提出了非瓶颈能力界定方法,给出了不同扰动水平下每台非瓶颈机器的生产能力、保护能力和云服务能力,为企业自制与云服务能力划分与利用提供了决策依据。     

多层级装配作业车间等量分批策略与调度算法

针对多层级装配作业车间中差异化零部件的加工装配进度协同极为困难的问题,通过零部件合理分批来提升车间的流动性,进行更灵活的进度协同并缩短生产周期,给出了此类车间最小化Makespan的分批调度模型;提出加工/装配阶段的分批策略,以及基于可行域搜索的改进型遗传算法,其初始种群生成及交叉变异考虑了批量变化带来的约束动态性,能...     

Scheduling sequence-dependent setup time job shops with preventive maintenance

Although many researchers have proposed different techniques to integrate production scheduling and preventive maintenance, these techniques have some drawbacks. For example, some of them are so intricate that one cannot easily implement them, or some strongly exploit specific features of the original studied problem that one cannot apply them to other problems. We hereby propose two techniques that are easy to understand and code, yet simplistically adaptable to any other machine-scheduling problems. This paper investigates job shop scheduling with sequence-dependent setup times and preventive maintenance policies. The optimization criterion is to minimize makespan. Four metaheuristics based on simulated annealing and genetic algorithms as well as adaptations of two metaheuristics in the literature are employed to solve the problem. The performances of the proposed algorithms are evaluated by comparing their solutions through two benchmarks based on Taillard’s instances.     

A memory-based complete local search method with variable neighborhood structures for no-wait job shops

In this paper, the strongly NP-hard no-wait job shop problem with makespan minimization is considered. By alternatively adopting the “as early as possible” strategy or the “as late as possible” rule, an alternative delay timetabling method is constructed. The sequencing and timetabling subproblems are optimized simultaneously by calculating timetables using the proposed alternative method according to a given binary string. By integrating variable neighborhood structures, a new local search method, complete local search with memory and variable neighborhood structure (CLMMV), is presented for the considered problem. CLMMV is compared with the existing best method complete local search with limited memory (CLLM) for the considered problem on both small- and large-size benchmark instances. Experimental results show that CLMMV is similar to CLLM on effectiveness and CLMMV is much more efficient than CLLM.     

A conflict-based priority dispatching rule and operation-based approaches to job shops

Job shop scheduling (JSS) problems consist of a set of machines and a collection of jobs to be scheduled. Each job consists of several operations with a specified processing order. In this paper, a job shop model problem is scheduled with the help of the Giffler and Thompson algorithm using a priority dispatching rule (PDR). A conflict based PDR is used to schedule the job shop model by using Genetic Algorithms (GAs). An iterative method is applied to the job model to find the optimal conflict-based PDR order and the operation sequence. The same job shop model is also scheduled based on an operation using simulated annealing (SA) and hybrid simulated annealing (HSA). A makespan of the job model is used as an objective. These four methods are considered as different solutions for each problem. A two-way analysis of variance (ANOVA) is applied to test its significance.     

随机工时下柔性加工车间的鲁棒优化调度方法

为了提高柔性加工车间调度方案的可行性、保障生产过程的稳定性,提出一种鲁棒优化调度方法。引入两个不确定参数来描述随机工时的波动程度和约束条件的允许违背程度,提出随机变量服从概率分布时一般线性规划问题的鲁棒优化方法。采用该方法将含随机工时而难以求解的随机型柔性加工车间调度模型转化为确定型鲁棒对等模型。基于该模型,将随机工时融入适应度函数中,结合遗传进化的全局优化和邻域搜索的空间拓展能力研制出鲁棒调度算法,同步实现工件排序和机器分配的双重决策。案例测试表明,所提方法可以在较短计算时间内、以较小性能损失、将近95%的置信度获得当前最优解。     

A constructive heuristic for the integrated scheduling of machines and multiple-load material handling equipment in job shops

This paper extends the traditional job shop scheduling problem (JSP) by incorporating the routing and scheduling decisions of the material handling equipment. It provides a generic definition and a mixed integer linear programming model for the problem considering the case of heterogeneous multiple-load material handling equipment. A constructive heuristic is developed for solving the problem. This heuristic is based on the well-known Giffler and Thompson’s algorithm for the JSP with modifications that account for the routing decisions of the material handling equipment and their effect on the start times of the manufacturing operations. Different dispatching rules are integrated into the heuristic, and experiments are conducted to study their effect on the makespan along with the determination of the computational time requirements of the developed heuristic.     

Scheduling multi-objective job shops using a memetic algorithm based on differential evolution

In this paper, a memetic algorithm based on differential evolution (DE), named MODEMA, is proposed for multi-objective job shop scheduling problems (MJSSPs). To balance the exploration and exploitation abilities, both DE-based global search and an adaptive local search are designed and applied simultaneously in the proposed MODEMA. Firstly, a smallest-order-value (SOV) rule is presented to convert the continuous values of individuals (real vectors) in DE to job permutations. Secondly, after the exploration based on DE, several neighborhoods are used in a local search and an adaptive Meta-Lamarckian strategy is employed to dynamically decide which neighborhood should be selected to stress exploitation in each generation. In addition, a solution set is used in MODEMA to hold and update the obtained nondominated solutions. Simulation results and comparisons with Ishibuchi and Murata’s multi-objective genetic local search (IMMOGLS) show the effectiveness and robustness of the proposed MODEMA.     

A fuzzy-neural approach for optimizing the performance of job dispatching in a wafer fabrication factory

A fuzzy-neural approach is presented in this study to optimize the performance of job dispatching in a wafer fabrication factory. The traditional optimization methods in this field have a few problems. To tackle these problems, we performed several treatments. First, we applied a more effective fuzzy-neural approach to estimate the remaining cycle time of a job. Then we established a systematic procedure to determine the optimal values of the parameters in the two-factor tailored nonlinear fluctuation smoothing rule for the mean cycle time, in order to optimize the scheduling performance. To assess the effectiveness of the proposed methodology, we conducted a production simulation. According to the experimental results, the proposed methodology is better than the existing approaches in optimizing the average cycle time.     

Performance evaluation of priority dispatching rules in multi-level assembly job shops with jobs having weights for flowtime and tardiness

The problem of scheduling in dynamic shops is an important operational problem in view of its complexity and significance in terms of associated costs of scheduling. While a number of research studies have investigated the problem of scheduling in flow shops and job shops, only some attempts have been done to study the problem of scheduling in assembly job shops that manufacture multi-level jobs. The problem of scheduling in dynamic assembly job shops with jobs having weights for holding and tardiness of jobs deserves due attention. In this study an attempt has been made to propose new priority dispatching rules that minimize the performance measures related to weighted flowtime and weighted tardiness of jobs. The existing unweighted dispatching rules have been modified in view of the consideration of weights for flowtime and tardiness of jobs. The performances of the (modified) existing dispatching rules and the proposed dispatching rules are compared through exhaustive simulation experiments with the consideration of a number of different experimental settings involving due-date setting, utilization levels and types of job structures. The proposed dispatching rules are found to perform better than the existing ones in most experimental settings and with respect to a number of measures of performance.     

高精加工中的刀具夹持技术

本文综述了高精加工中用的刀具夹持技术,同时提出了在实际应用中如何正确选择刀具夹持系统的看法。     

Improved solutions for job shop scheduling problems through genetic algorithm with a different method of schedule deduction

This paper details the studies on the use of single mesh size garnet abrasives in abrasive waterjet machining for cutting aluminum. The influence of three different single mesh size abrasives, pressure, traverse rate, and abrasive flow rate; on depth of cut, top kerf width, bottom kerf width, kerf taper, and surface roughness are investigated. Experiments designed using standard L9 orthogonal array and the analysis of variance helped in the determination of highly significant, significant and weakly significant cutting parameters. Single mesh size abrasives are found to yield decreased surface roughness than multi mesh size abrasives. Based on these studies, response equations are developed to predict the target parameters. Using single mesh abrasives, a practitioner not only can cut faster but also achieve reduced surface roughness.     

A tabu search-based heuristic for single-product lot streaming problems in flow shops

Lot streaming is a technique that splits a production lot consisting of identical items into sublots to improve the performance of a multistage production system by overlapping the sublots on successive machines. In this study, a single-product multistage stochastic flow shop problem with consistent sublot types and discrete sublot sizes is considered, and a heuristic algorithm which is a combination of simulation and tabu search is presented with the objective of minimizing makespan. First, the performance of the proposed heuristic is evaluated against a deterministic model, then it is applied to stochastic flow shops and the results are compared with those of Arena’s OptQuest. The computational results show that the proposed heuristic gives rather efficient results and facilitates the solution of the considered complex stochastic lot streaming problems.     

An efficient bi-objective heuristic for scheduling of hybrid flow shops

This paper considers the problem of scheduling n independent jobs in hybrid flow shop environment with sequence-dependent setup times to minimize the makespan and total tardiness. For the optimization problem, an algorithm namely; bi-objective heuristic (BOH) is proposed for searching Pareto-optimal frontier. The aim of the proposed algorithm is to generate a good approximation of the set of efficient solutions. The BOH procedure initiates by generating a seed sequence. Since the output results are strongly dependent on the initial solution and in order to increase the quality of output results algorithm, we have considered how the generation of seed sequence with random way and particular sequencing rules. Two methods named Euclidean distance and percent error have been proposed to compare non-dominated solution sets obtain of each seed sequence. It is perceived from these methods that the generation of seed sequence using earliest due date rule is more effective. Then, the performance of the proposed BOH is compared with a simulated annealing proposed in the literature and a VNS heuristic on a set of test problems. The data envelopment analysis is used to evaluate the performance of approximation methods. From the results obtained, it can be seen that the proposed algorithm is efficient and effective.     

Robust metaheuristics for group scheduling with sequence-dependent setup times in hybrid flexible flow shops

This paper considers group scheduling problem in hybrid flexible flow shop with sequence-dependent setup times to minimize makespan. Group scheduling problem consists of two levels, namely scheduling of groups and jobs within each group. In order to solve problems with this context, two new metaheuristics based on simulated annealing (SA) and genetic algorithm (GA) are developed. A design procedure is developed to specify and adjust significant parameters for SA- and GA-based metaheuristics. The proposed procedure is based on the response surface methodology and two types of objective function are considered to develop multiple-objective decision making model. For comparing metaheuristics, makespan and elapsed time to obtain it are considered as two response variables representing effectiveness and efficiency of algorithms. Based on obtained results in the aspect of makespan, GA-based metaheuristic is recommended for solving group scheduling problems in hybrid flexible flow shop in all sizes and for elapsed time SA-based metaheuristic has better results.     

基于多代理机制的车间制造资源调度管理系统的研究

在分析车间制造资源调度特点的基础上,综合运用多代理机制、规则调度和消息通信机制等技术,建立了适应制造企业车间层生产环境的多代理模型结构。重点研究了多代理机制的实现、基于多代理结构下的通信机制和规则调度机制等关键技术,构建了基于客户机／服务器结构车间制造资源的调度管理系统的体系结构,研究了其工作流程和实现方法,并开发了基于多代理的车间制造资源调度管理仿真系统。