An integrated scheduler for manufacturing planning and control (INSCH)

The most basic problem in a manufacturing process is to create valid scheduling system which determines the sequence of jobs to be processed at each of the series of machine centers. An integrated scheduler (INSCH) is developed for small job shop manufacturing systems while considering high machine utilization, low work-in-process, and reduced job lateness.

As an and to understand the interaction of live jobs with the shop, sequence scheduler is developed to complement production scheduler such as Gantt bar chart. INSCH can achieve better performance than simple static models as shown in an example. It is desirable for INSCH to be applied to small job shop manufacturing companies using micro personal computer with relevant modifications discussed.     

Customized job shop scheduling application development

This paper discusses development of a customized job shop scheduling application. Effective shop floor control relies heavily on the scheduling of part production through work centers. Production without part schedules and sequences is inefficient for job shops. Standard off-the-shelf scheduling software will typically not do the job. Customized scheduling software was developed to both increase manufacturing control while meeting all the requirements of a job shop's production processes, using the least slack rule for sequencing parts in order to meet final assembly schedules.     

Skill based manufacturing vs. “unmanned factory”—which is superior?

Past development of small batch production has led to advanced horizontal and vertical division of labor, job shop manufacturing, and the use of NC machines. This has caused serious difficulties such as long and variant throughput times, an unfavorable ratio of unproductive to productive workers, and low quality of work. Additionally confronted with deeply changed market conditions, the management is split over the right answer to this challenge. Most managers and production planners try to replace human work still further by enforced use of computers on the shop floor and in the technical office in an integrated manner (CIM). Since this strategy is very likely to create new severe problems, the minority seeks to avoid them by reorganizing production and rearranging the division of functions between humans and machines profoundly (skill based manufacturing). This position is outlined in this paper in some detail and examples of realized subsystems, as first steps on this development path, are included. Finally, reasons for its superiority and resistance to implement it are discussed.     

大数据环境下MES作业计划与调度能力云服务化研究

云制造技术给制造企业带来机遇的同时,也为其制造执行系统MES的设计与实现带来了新的挑战。为了解决单件小批MES中作业计划与调度优化问题,首先设计了一个从作业计划静态制定,到作业执行情况实时监控与主动感知,再到异常事件智能响应,最后到作业调度动态调节的闭环体系结构。接着针对异常信息实时获取与异常事件发现、异常事件智能化处理以及作业计划与调度优化算法计算能力服务化三个子问题,依次进行了问题分析并给出了技术解决方案。最后,以哈尔滨电机厂为案例对象,综合利用IEC/ISO 62264标准、大数据分析与挖掘方法以及由虚拟化、服务化和SOA等组成的云计算技术实现了单件小批MES作业计划与调度综合优化系统,验证了上述理论与方法的有效性。     

The automated manufacturing research facility of the national bureau of standards

A major facility for manufacturing research is being established at the National Bureau of Standards (NBS). The facility is designed to provide extreme flexibility and to be capable of emulating a wide variety of manufacturing cells typical of a small machine job shop. The control architecture adopted is hierarchical in nature and highly modular. The facility will be used for research on interface standards and metrology in an automated environment.     

基于赋时事件图的周期可重构流水作业构形建模与优化

Based on the idea that modules are independent of machines, different combinations of modules and machines result in different configurations and the system performances differ under different configurations, a kind of cyclic reconfigurable flow shops are proposed for the new manufacturing paradigm—reconfigurable manufacturing system. The cyclic reconfigurable flow shop is modeled as a timed event graph. The optimal configuration is defined as the one under which the cyclic reconfigurable flow shop functions with the minimum cycle time and the minimum number of pallets. The optimal configuration, the minimum cycle time and the minimum number of pallets canbe obtained in two steps.     

Production sequencing problem with reentrant work flows and sequence dependent setup times

This paper addresses a shop scheduling problem for the side frame press shop in a truck manufacturing company. In the problem, a set of n jobs to be scheduled on two machines. All the jobs require processing by the first machine more than once in their operation sequences with reentrant work flows. An unusual aspect of the problem is that the setup times required for a job in the first machine depend not on the immediately preceding job but on the job which is two steps prior to it. Redefining the job elements, the problem is formulated into a general two machine flow shop problem which has a set of job-element precedence constraints. The problem is solved with a modified dynamic programming with the objective of the minimum makespan. An optimal schedule is found utilizing the sequence dominance condition and a decision-delay scheme. A numerical example is presented for the illustration purpose.     

A knowledge-based expert system for technology acquisition in small and medium scale manufacturing organizations

Consistent and reliable decision making for technology acquisition in small and medium scale manufacturing organizations is vitally important since these firms are the backbone of national economies, both in developed and developing countries. Because of their flexibility, small and medium scale firms are successful in adopting new technologies. However, a careful analysis should be conducted in technology acquisition decisions. Since these decisions require special type of knowledge and expertise, expert system, as an important tool of computerized decision making, can overcome these multidimensional difficulties.

This paper proposes a knowledge-based approach making use of issues such as sales, processes, costs and general policies, in decision processes for technology acquisition by small and medium scale manufacturing organizations in the developing environments.     

A Decision Support System for a small scale industry in a developing country

This paper describes the design and development of a Decision Support System (DSS) for a small scale manufacturing company in a developing country. The DSS provides a solution for an integrated problem of planning, shopfloor scheduling, and control. The DSS system accepts the demand data with priorities, then uses the information from the imbedded data base system regarding product structure, production process, available resources with the status, and inventory. This in turn is used by the imbedded models to solve planning and scheduling problems, and provide solutions containing job order release, shopfloor scheduling and material requirement report. What if analysis feature provided by DSS allows the managers to incorporate their knowledge and experience to improve the quality of the solution by evaluating different scenarios presented by the manager. The laboratory equipment manufactured by the company is made to order. Product information regarding twenty-two high demand items is incorporated into the data base system, and the scheduling problem is solved for these items. The jobshop is a mixed shop problem containing a flow shop, an open shop, and a flow shop. A heuristic method used for solving this problem is presented.     

An expert system for the selection of scheduling rules in a job shop

This paper presents a conceptual framework for the application of expert systems for the selection and development of scheduling rules for a job shop. A portion of the framework is illustrated using an expert system developed using MI™.     

相关工件车间调度问题的拓扑算法

针对加工装配型离散制造企业实际生产的特点,提出了一类用于表示工序之间偏序关系的相关工件车间调度问题。为了利用已有的求解表示工序之间的线序关系的传统车间调度算法求解相关工件车间调度问题,设计了一种拓扑算法,该算法能够将工序之间的偏序关系转化为线序关系,将相关工件车间调度问题转化为传统的车间调度问题,通过实证研究,结果表明了拓扑算法是可行和高效的。     

知识获取方法DECO

知识获取方法学是目前人工智能领域中最重要的分支之一,现在已出现了几种不同应用范围的获取方法,集成式知识获取方法的研究已成为当前的一种趋势,本文所介绍的DECO方法是一种集成式方法,它将知识获取分为若干个基本上相互独立的步骤,并且溶进了知识库快速生成技术以及基于专家分析实例的学习方法。     

Digital twin-based job shop anomaly detection and dynamic scheduling

Scheduling scheme is one of the critical factors affecting the production efficiency. In the actual production, anomalies will lead to scheduling deviation and influence scheme execution, which makes the traditional job shop scheduling methods are not sufficient to meet the needs of real-time and accuracy. By introducing digital twin (DT), further convergence between physical and virtual space can be achieved, which enormously reinforces real-time performance of job shop scheduling. For flexible job shop, an anomaly detection and dynamic scheduling framework based on DT is proposed in this paper. Previously, a multi-level production process monitoring model is proposed to detect anomaly. Then, a real-time optimization strategy of scheduling scheme based on rolling window mechanism is explored to enforce dynamic scheduling optimization. Finally, the improved grey wolf optimization algorithm is introduced to solve the scheduling problem. Under this framework, it is possible to monitor the deviation between the actual processing state and the planned processing state in real time and effectively reduce the deviation. An equipment manufacturing job shop is taken as a case study to illustrate the effectiveness and advantages of the proposed framework.     

The client-centred approach: expert system development

Abstract: This paper describes a project that is studying an expert system (ES) development method tailored to meet the requirements of small and medium-sized enterprises (SMEs). It is posited that many such organisations cannot use ES technology because of its high entry price and because the available tools and methods were developed for and by large organisations. Within this context our development method encompasses the entire life cycle of an ES from initial conception to implementation through to maintenance and updating. The central premise is that the method should be 'client-centred', emphasising what the client can see, rather than being 'technology-centred', emphasising how the knowledge engineers work. Discussion includes how this methodology addresses many criticisms of current ES development methods, including rapid prototyping and KADS.     

Experiences with an expert systems prototyping methodology

Abstract: Although the benefits of knowledge-based expert systems (ES) and experiences with the methods, techniques and tools employed in knowledge engineering have been extensively reported, less is known about experiences with development and development methodologies. Although ES development is frequently associated with prototyping, a growing number of specific development methodologies have been proposed and are in use. Using information on four development projects at General Electric Industrial and Power Systems, this paper reports on the use of a variation of a prototyping methodology. It identifies some of the advantages, disadvantages and effects of using this approach to development. It raises a number of issues that future ES development methodologies will have to address.     

Computational complexity of determining resource loops inre-entrant flow lines

This paper presents a comparison study of the computational complexity of the general job shop protocol and the more structured flow line protocol in a flexible manufacturing system. It is shown that the representative problem of finding resource invariants is NP-complete in the case of the job shop, while in the flow line case it admits a closed form solution. The importance of correctly selecting part flow and job routing protocols in flexible manufacturing systems to reduce complexity is thereby conclusively demonstrated     

Holonic job shop scheduling using a multiagent system

Manufacturing job shop scheduling is a notoriously difficult problem that lends itself to various approaches - from optimal algorithms to suboptimal heuristics. We combined popular heuristic job shop-scheduling approaches with emerging AI techniques to create a dynamic and responsive scheduler. We fashioned our job shop scheduler's architecture around recent holonic manufacturing systems architectures and implemented our system using multiagent systems. Our scheduling approach is based on evolutionary algorithms but differs from common approaches by evolving the scheduler rather than the schedule. A holonic, multiagent systems approach to manufacturing job shop scheduling evolves the schedule creation rules rather than the schedule itself. The authors test their approach using a benchmark agent-based scheduling problem and compare performance results with other heuristic-scheduling approaches.     

任务分解控制及人员柔性的车间集成调度

针对复杂产品制造环境下制造任务分解与资源配置脱节的问题,提出了制造任务分解与多目标人员柔性车间资源配置优化方法。在对复杂制造任务特点进行分析的基础上,建立了任务分解粒度控制模型和考虑人员柔性的制造单元资源模型,利用自适应非支配排序遗传算法进行求解,得到了较为满意的任务分解和车间资源调度方案。     

Recurrent neural network approach for cyclic job shop scheduling problem

While cyclic scheduling is involved in numerous real-world applications, solving the derived problem is still of exponential complexity. This paper focuses specifically on modelling the manufacturing application as a cyclic job shop problem and we have developed an efficient neural network approach to minimise the cycle time of a schedule. Our approach introduces an interesting model for a manufacturing production, and it is also very efficient, adaptive and flexible enough to work with other techniques. Experimental results validated the approach and confirmed our hypotheses about the system model and the efficiency of neural networks for such a class of problems.