An efficient heuristic for scheduling batches of parts in a flexible flow system

Flexible manufacturing systems (FMSs) are a class of automated systems that can be used to improve productivity in batch manufacturing. Four stages of decision making have been defined for an FMS—the design, planning, scheduling, and control stages. This research focuses on the planning stage, and specifically in the area of scheduling batches of parts through the system.The literature to date on the FMS planning stage has mostly focused on the machine grouping, tool loading, and parttype selection problems. Our research carries the literature a step further by addressing the problem of scheduling batches of parts. Due to the use of serial-access material-handling systems in many FMSs, the batch-scheduling problem is modeled for a flexible flow system (FFS). This model explicitly accounts for setup times between batches that are dependent on their processing sequence.A heuristic procedure is developed for this batch-scheduling problem—the Maximum Savings (MS) heuristic. The MS heuristic is based upon the savings in time associated with a particular sequence and selecting the one with the maximum savings. It uses a two-phase method, with the savings being calculated in phase I, while a branch-and-bound procedure is employed to seek the best heuristic solution in phase II. Extensive computational results are provided for a wide variety of problems. The results show that the MS heuristic provides good-quality solutions.     

A decision-making approach to the operation of flexible manufacturing systems

This paper introduces a generic decision-making framework for assigning resources of a manufacturing system to production tasks. Resources are broadly defined production units, such as machines, human operators, or material handling vehicles; and tasks are activities performed by resources. In the specific context of FMS, resources correspond to individual machines; tasks correspond to operations to be performed on parts. The framework assumes a hierarchical structure of the system and calls for the execution of four consecutive steps to make a decision for the assignment of a resource to a task. These steps are 1) establishment of decision-making criteria, 2) formation of alternative assignments, 3) estimation of the consequences of the assignments, and 4) selection of the best alternative assignment. This framework has been applied to an existing FMS as an operational policy that decides what task will be executed on which resource of this FMS. Simulation runs provide some initial results of the application of this policy. It is shown that the policy provides flexibility in terms of system performance and computational effort.     

在嵌入式系统中实现热备份

在要求高可靠性的系统设计中要求系统能够实现双机热备份,从而保证在出现问题时能够快速恢复服务。详细解读了在开发的调度机中如何实现热备份。     

Grid resource brokering algorithms enabling advance reservations and resource selection based on performance predictions

We present algorithms, methods, and software for a Grid resource manager, that performs resource brokering and job scheduling in production Grids. This decentralized broker selects computational resources based on actual job requirements, job characteristics, and information provided by the resources, with the aim to minimize the total time to delivery for the individual application. The total time to delivery includes the time for program execution, batch queue waiting, and transfer of executable and input/output data to and from the resource. The main features of the resource broker include two alternative approaches to advance reservations, resource selection algorithms based on computer benchmark results and network performance predictions, and a basic adaptation facility. The broker is implemented as a built-in component of a job submission client for the NorduGrid/ARC middleware.     

A modified teaching–learning-based optimisation algorithm for bi-objective re-entrant hybrid flowshop scheduling

In this paper, a modified teaching–learning-based optimisation (mTLBO) algorithm is proposed to solve the re-entrant hybrid flowshop scheduling problem (RHFSP) with the makespan and the total tardiness criteria. Based on the simple job-based representation, a novel decoding method named equivalent due date-based permutation schedule is proposed to transfer an individual to a feasible schedule. At each generation, a number of superior individuals are selected as the teachers by the Pareto-based ranking phase. To enhance the exploitation ability in the promising area, the insertion-based local search is embedded in the search framework as the training phase for the TLBO. Due to the characteristics of the permutation-based discrete optimisation, the linear order crossover operator and the swap operator are adopted to imitate the interactions among the individuals in both the teaching phase and the learning phase. To store the non-dominated solutions explored during the search process, an external archive is used and updated when necessary. The influence of the parameter setting on the mTLBO in solving the RHFSP is investigated, and numerical tests with some benchmarking instances are carried out. The comparative results show that the proposed mTLBO outperforms the existing algorithms significantly.     

Distributed artificial intelligence for FMS scheduling, control and design support

The aim of this paper is to point out some of the abilities of Distributed Artificial Intelligence in the domain of scheduling, control and design support of Flexible Manufacturing Systems. A distributed management system is proposed, based on Distributed Problem Solving, sub-field of Distributed Artificial Intelligence. The basic concepts are the concept of Resource Management Entity to ensure local optimization of the management of resources and the concept of cooperation to provide ability for global and local consistency. The management of resources is associated to activities such as scheduling, control or simulation. It is shown that this system computes not only practicable schedulings, but also presents, on the one hand, some abilities in supporting the design and the robust optimization of Flexible Manufacturing Systems, and, on the other hand, some abilities in supporting real-time control of such systems. This enables, in future works, to design a Distributed Decision Support System for integrated scheduling, control and design support of production systems.     

Work organisation constructs and ergonomic outcomes among European forest machine operators

The aims of the study were to: 1) create work organisation constructs for forest machine operators; 2) examine relationships between these work organisation constructs and different ergonomic outcomes. The study was carried out among forest machine operators in six European countries and was based on a questionnaire survey (n = 358). Exploratory factor analysis (EFA) was used in the formation of the construct measures of work organisation. The EFA resulted in a five-factor structure. The factors were named ‘job control’, ‘variation’, ‘job rotation’, ‘breaks’ and ‘rate of work’. Three multiple regression analyses were carried out separately for the dependent variables job satisfaction, musculoskeletal symptoms and headache/sleeping problems. All regression analyses resulted in significant overall models. The highest explained variance among the dependent variables was found for job satisfaction (R = 0.51, i.e. ‘large’ effect size). The unique contribution of the work organisation constructs varied in the models, but ‘job rotation’ contributed significantly in all regression models. The results may be used as a source for ergonomic improvements to work organisation. The present study was performed as part of the EU project ‘ErgoWood’, which resulted in a European handbook for mechanised forest operations (Gellerstedt et al. 2005 Gellerstedt S. Lidén E. Bohlin F Health and performance in mechanised forest operations The Swedish University of Agricultural Sciences, Department of Forest Products and Markets Uppsala 2005  [Google Scholar]). The results delivered part of the evidence base for a toolbox in this handbook regarding changes in work organisation to improve health and performance.     

Domain–Specific High–Level Modeling and Synthesis for ATM Switch Prototyping

ATM switch, the core technology of an ATM networking system, is one of the major products in Fujitsu telecommunication business. However, current gate–level design methodology can no longer satisfy its stringent time–to–market requirement. It becomes necessary to exploit high–level methodology to specify and synthesize the design at an abstraction level higher than logic gates. This paper presents our prototyping experience on domain–specific high–level modeling and synthesis for Fujitsu ATM switch design. We propose a high–level design methodology using VHDL, where ATM switch architectural features are considered during behavior modeling, and a high–level synthesis compiler, MEBS, is prototyped to synthesize the behavior model down to a gate–level implementation. Since the specific ATM switch architecture is incorporated into both modeling and synthesis phases, a high–quality design is efficiently derived. The synthesis results shows that given the design constraints, the proposed high–level design methodology can produce a gate–level implementation by MEBS with about 15 percent area reduction in shorter design cycle when compared with manual design.     

工作危害分析法在蜡油催化裂化装置的应用

在催化裂化装置停工消缺的全过程中．全面应用工作危害分析法，细化每一项工作，分析潜在的危害，找出主要危害及其后果，制定控制措施，并抓好具体落实，确保检修工作的顺利进行。应用结果表明，装置各专业管理人员的共同参与，使分析结果充分全面，措施合理、可操作性强；删除了原表格中风险度一栏，使分析表的指导作用更强，也提高了应用水平；应用该方法，使管理、操作人员正确识别危害与风险，提高了管理与操作的水平。并找出存在的不足，提出了改进意见。     

基于加气站槽车调度的模型建立与算法研究

通过对CNG的发展形势介绍,深入到要研究的具体问题——槽车调度,槽车调度就是加气站母站向子站调度发送槽车。匈牙利算法是用到线性规划上解决最优化最优解的问题。考虑到槽车调度优化的问题的特殊性,因此在匈牙利算法的思想基础上,提出了最大差值法。此方法能更高效率地运算出最优解。