计算机辅助编制车间作业调度系统

本文详细阐述了车间作业计划的计算机辅助编制系统的实现原理和过程。针对车间作业优化调度问题，建立了新的数学描述模型，提出了一种新的启发式优先规则，形成相应的计算机仿真模型。该系统模块化结构强，人机界面友好，经过实际运行，结果令人满意，为企业实施计算机管理提供了有效工具。     

基于成本的车间作业优化模型及实证研究

介绍车间作业优化问题,探讨作业、成本的关系并构建作业成本计算模型,将作业成本法与作业优化理论相结合,提出基于成本的作业优化模型,并使用该模型进行了企业实证研究,分析了作业成本法下作业优化模型的实际使用效果。     

作业车间的模糊动态调度问题研究

本文针对作业车间的模糊动态调度问题,给出了该问题的生产系统描述、建模,给出了基于工件到达时间三角模糊数的计算确定重调度时段划分点的模糊动态调度策略,通过一种基于时间分解的策略将作业车间的模糊动态调度问题转化为一系列不一定被完全执行的静态模糊子调度问题求解。针对模型的求解给出了改进的G&T算法,将改进的基于关键路径的邻域交换技术引入遗传算法变异算子的设计,改善了算法解的局部寻优能力。仿真实验结果表明,本文给出的作业车间模糊动态调度模型是正确的,提出的算法有效,且动态调度策略具有鲁棒性。     

基于作业成本法的修船企业成本管理体系——以某船务工程有限公司船体车间为例

本文以某修船公司船体车间为例,分析了实施作业成本法的可能性,介绍了实施作业成本法的步骤,并构建了作业成本管理核算体系,总结了作业成本法在实施过程中的经验。     

某服装缝制车间前片缝制的作业分析

在该论文中,针对服装的前片缝制的工序中出现的物料摆放、动作浪费及效率低下的问题,运用IE作业分析方法并结合生产车间的录像,通过双手操作程序图进行改善。希望合理改善物料的摆放,科学的动作以减轻员工的动作幅度,降低疲劳,提高前片缝制的效率。结合改善后的效果,为制定出一套合乎标准的动作规范做些参考。     

基于作业成本法的ERP综合效益评价研究

根据企业资源计划(ERP)实施效益评价特点,基于作业成本法的核心理念,文章建立了ERP综合效益评价体系,涵盖了ERP应用性评价、经济性评价、风险性评价三部分内容,为ERP综合效益评价提供了思路和方法,为企业有效实施ERP提供科学的决策依据。     

制造企业多品种成批型生产经营计划的编制方法

本文首先分析了制造企业多品种成批型生产经营计划编制问题的特点，提出了将知识模型、数学模型和决策者相结合编制生产经营计划的方法。在此基础上，建立了年出产计划数学模型，以求解产品出产量和产品组持续出产期优化问题，提出了一种启发式的优化方法，并研究了由年出产计划制订月出产计划的方法。实际应用结果表明该计划编制方法是实用有效的。     

炼油化工企业基于作业链网的分步作业成本法

炼油化工企业的各个作业之间相互联结,前后有序,呈网状结构,形成作业链网.本文以作业成本计算理论为基础,根据炼化企业的生产特点和管理要求,提出了基于作业链网的分步作业成本计算理论.通过确定作业链网、建立分步作业成本计算模型,计算各步骤与各种产品的作业成本,从而提供产品、作业成本信息以及作业链网的详细成本信息,为决策提供支持.     

作业成本法在邮政企业的应用问题研究

中国邮政面临体制改革、信息技术对传统邮政业务替代、市场竞争日趋激烈等各种挑战,邮政企业采用传统方法提供的成本信息越来越不能适应内外部环境的变化。我们需要探索新的成本核算方法以清晰内部成本,找到降本增效,提高竞争能力的新途径。作业成本法具有成本计算和成本管理两大功能,不仅可以提供相对准确的成本信息,还可依据作业链和价值链的分析,进行成本管理,满足经营控制的需要。作业成本法能够提供更加科学准确的成本信息,更好地支撑经营决策,深化企业的全面预算管理,邮政企业应用作业成本法有其现实需要。作业成本法的应用也要有一定的基础条件,从企业特点看,邮政企业应用作业成本法具有一定的可行性。本文还对邮政企业应用作业成本法的难点进行了分析,难点主要在流程统一、成本归集和作业采集等几方面。本文对中国邮政应用作业成本法提出建议,认为邮政企业实施作业成本法可以按照先粗后细、先易后难、突出重点、逐步深化的原则,先在较短时期内建立起作业成本法的概念,取得初步效果,再根据管理要求和客观条件逐步深化。本文还对确认主要作业、归集作业成本、采集作业动因和作业成本核算结果的应用等问题提出了初步解决思路。     

知识作业过程管理方法的探讨

本文基于认知科学的理论和IE的预定时间标准法PTS原理,提出了知识作业过程的"动素"--心智操作(mind operations, MO)解析思路,把知识作业过程分解为MO,并通过案例解析把MO链还原为知识作业过程;进而,构造了MO概念集及其要素之间关系的结构模型假设,对模型假设进行了样本数据的验证性分析,其结果支持知识作业过程可用九要素的MO概念集全模型进行表征,为知识作业过程管理的方法优化和作业测定提出了心智操作分析思路.这同时也蕴涵着对人工智能知识表示方法的探讨.     

A mathematical model for job shop scheduling with multiple process plan consideration per job

In this paper, a mixed integer programming model is formulated for scheduling a set of jobs through a shop when each job is supplied or provided with multiple process plans or process routings. Simultaneous selection of a process plan for each job and the sequencing of the jobs through the machines in the shop based on the set of selected process plans is addressed. The procedure developed seeks to integrate the selection of machines for each job and the sequencing of jobs on each machine based on the objective of minimizing production makespan. the application of the procedure is demonstrated with an example problem. The following conclusions were drawn as a result of the research: (1) the procedure developed produces optimal or near optimal solution; (2) the benefit from the developed approach is that it allows a shop to adaptively select process plans for jobs to optimize on production makespan. By combining solution quality with scheduling flexibility and efficiency, the productivity of a shop can be greatly enhanced.     

Multi-objective permutation flow shop scheduling problem: Literature review,classification and current trends

The flow shop scheduling problem is finding a sequence given n jobs with same order at m machines according to certain performance measure(s). The job can be processed on at most one machine; meanwhile one machine can process at most one job. The most common objective for this problem is makespan. However, many real-world scheduling problems are multi-objective by nature. Over the years there have been several approaches used to deal with the multi-objective flow shop scheduling problems (MOFSP). Hence, in this study, we provide a brief literature review of the contributions to MOFSP and identify areas of opportunity for future research.     

A comparative analysis of due date based job sequencing rules in a flow shop with multiple processors

The literature on job scheduling recognizes the importance of due date performance criteria such as mean tardiness and maximum tardiness. A number of studies test a large number of sequencing rules for these criteria in job shop and flow shop settings. The object of this present research is to examine the performance of some well-known priority rules in a flow shop with multiple processors. This study investigates the performance of ten priority rules in terms of mean and maximum tardiness. It examines the effects of problem characteristics, such as number of jobs, number of machines stages and number of parallel processors at each stage, and the performance of priority rules using regression analysis. The findings of the study suggest that the primary determinants of tardiness-based criteria are problem characteristics. In addition, both the regression analysis and the analysis of variance provide strong evidence of the strategy-effect. Finally, a detailed performance review of examined priority rules for various problem characteristics is presented.     

The Creation of Output and Quality in Services: A Framework to Analyze Information Technology‐Worker Systems

Information technology has profoundly impacted the operations of firms in the service industry and service environments within manufacturing. Two models are introduced that establish a conceptual framework linking firm profit to attributes of the IT‐worker system. The framework considers the impact of IT capabilities (such as functionality and ease‐of‐use) and worker skill as drivers of output volume and quality. The framework contrasts attributes of the IT‐worker systems when services are mass‐produced (flow shop) versus customized (job shop). Mathematical models are introduced to formalize the conceptual framework. Numerical examples are presented that illustrate the types of insights that can be obtained from the models.     

A multi-objective particle swarm for a flow shop scheduling problem

Flow shop problems as a typical manufacturing challenge have gained wide attention in academic fields. In this paper, we consider a bi-criteria permutation flow shop scheduling problem, where weighted mean completion time and weighted mean tardiness are to be minimized simultaneously. Since a flow shop scheduling problem has been proved to be NP-hard in strong sense, an effective multi-objective particle swarm (MOPS), exploiting a new concept of the Ideal Point and a new approach to specify the superior particle's position vector in the swarm, is designed and used for finding locally Pareto-optimal frontier of the problem. To prove the efficiency of the proposed algorithm, various test problems are solved and the reliability of the proposed algorithm, based on some comparison metrics, is compared with a distinguished multi-objective genetic algorithm, i.e. SPEA-II. The computational results show that the proposed MOPS performs better than the genetic algorithm, especially for the large-sized problems.     

The Flow Shop Scheduling Polyhedron with Setup Times

This paper addresses the problem of improving the polyhedral representation of a certain class of machine scheduling problems. Despite the poor polyhedral representation of many such problems in general, it is shown that notably tighter linear programming representations can be obtained for many important models. In particular, we study the polyhedral structure of two different mixed-integer programming formulations of the flow shop scheduling problem with sequence-dependent setup times, denoted by SDST flow shop. The first is related to the asymmetric traveling salesman problem (ATSP) polytope. The second is less common and is derived from a model proposed by Srikar and Ghosh based on the linear ordering problem (LOP) polytope. The main contribution of this work is the proof that any facet-defining inequality (facet) of either of these polytopes (ATSP and LOP) induces a facet for the corresponding SDST flow shop polyhedron. The immediate benefit of this result is that all developments to date on facets and valid inequalities for both the ATSP and the LOP can be applied directly to the machine scheduling polytope. In addition, valid mixed-integer inequalities based on variable upper-bound flow inequalities for either model are developed as well. The derived cuts are evaluated within a branch-and-cut framework.     

The sensitivity of job mix and load capacity bottlenecks on inventory and due date performance in a manufacturing system

Based on a benchmark job-lot manufacturing system a simulation study was carried out to compare the performance of just-in-time (JIT) shop control system Kanban with conventional job-shop control procedures. The shop control policies were tested under a good manufacturing environment and the effects of job mix and load capacity bottlenecks on various shop control policies were tested. From the simulation results, it is inferred that there are shop control procedures that perform better than the Kanban in a job shop. It has been observed that even with adequate capacity, bottleneck areas surface due to fluctuations in the shop load. Kanban is not appropriate in such a situation because capacity bottlenecks can significantly reduce the ell'ectiveness of a pull system. The disparateness in the processing requirements for jobs can seriously undermine the performance of the shop. This is the type of shop environment where the shop control procedures will be most effective. Although Kanban came out best when the load capacity bottlenecks and the disparateness of the job mix were removed, the selected shop control variable combinations closely approximated the Kanban result. Although many features of JIT can be implemented in any system, companies trying to adopt JIT should remember that Kanban requires a rigid system intolerant of any deviation.     

Workload Control and Order Release: A Lean Solution for Make‐to‐Order Companies

Protecting throughput from variance is the key to achieving lean. Workload control (WLC) accomplishes this in complex make‐to‐order job shops by controlling lead times, capacity, and work‐in‐process (WIP). However, the concept has been dismissed by many authors who believe its order release mechanism reduces the effectiveness of shop floor dispatching and increases work center idleness, thereby also increasing job tardiness results. We show that these problems have been overcome. A WLC order release method known as “LUMS OR” (Lancaster University Management School order release) combines continuous with periodic release, allowing the release of work to be triggered between periodic releases if a work center is starving. This paper refines the method based on the literature (creating “LUMS COR” [Lancaster University Management School corrected order release]) before comparing its performance against the best‐performing purely periodic and continuous release rules across a range of flow directions, from the pure job shop to the general flow shop. Results demonstrate that LUMS COR and the continuous WLC release methods consistently outperform purely periodic release and Constant WIP. LUMS COR is considered the best solution in practice due to its excellent performance and ease of implementation. Findings have significant implications for research and practice: throughput times and job tardiness results can be improved simultaneously and order release and dispatching rules can complement each other. Thus, WLC represents an effective means of implementing lean principles in a make‐to‐order context.     

Heterogeneous dispatching rules in job and flow shops

This paper reports the results of a study of the use of heterogeneous dispatching rules for the scheduling of work in a job shop. The methodology employed included discrete event simulation, using rule combinations determined by prior genetic algorithm searches and generalization using neural networks. Eight dispatching rules were considered, including first in first out (FIFO), earliest due date ( EDD), shortest processing time (SPT), slack/ number of operations (SLK), critical ratio (CR), modified due date (MDD), modified operation due date (MOD), and apparent tardiness cost (ATC). A three-machine job shop was studied, in which three work organizations were employed, pure flow (fixed sequence), pure job shop ( random sequence), and a hybrid shop where flow is random but with unequal probabilities. Three levels of machine loading were used and average tardiness was used as the performance measure. In most cases, modified due date and apparent tardiness cost were the best rules. The application of the best rules effected the results primarily when applied to bottleneck machines or the first machine in a pure flow shop. Nearly any other rule was acceptable on non-botdeneck machines except FIFO and CR, which consistently perform poorly. No major advantage of mixing rules was found.     

Overtime usage in a job shop environment

Problems are encountered in a job shop which has a fixed capacity if the total work content of the jobs passing through the shop increases sufficiently. Even the use of effective priority dispatching rules and/or expediting does not adequately shorten the queues which develop if the total work content continually exceeds shop capacity. To avoid losing job orders because the orders are unduly delayed, the job shop might resort to overtime usage. This study examines the efficient and economic use of overtime to relieve the backlog problem and uses overtime as the basic criterion for evaluation of overtime usage. The study employs GPSS V programming language to simulate a hypothetical job shop. The shop is loaded to various proportions of its normal capacity and various levels of overtime are tested. Findings show that overtime should not be assigned indiscriminately but rather should be based on a shop's unique conditions of overtime cost, the priority rule being employed, and the level of capacity utilization. Marginal benefit-cost ratio curves are developed to determine whether overtime usage is economically reasonable. These curves may also be used to determine the maximum or limiting amount of overtime to use under specific shop conditions.