Self-adaptive dynamic scheduling of virtual production systems

To enhance the agility of virtual production systems (VPSs) under today's dynamic and changing manufacturing environment, a self-adaptive dynamic scheduling method based on event-driven is proposed for VPSs in this paper. This method is composed of the mechanisms and algorithm of self-adaptive dynamic scheduling. In the mechanisms, the dynamic events faced by VPSs are determined through users’ inputs or supervisory controllers’ detections, the local effects made on the schedule are analysed according to the dynamic events, and the self-adaptive measures and rules are specified correspondingly. To implement the dynamic scheduling of VPSs under the guidance of self-adaptive rules, a modified heuristic rescheduling algorithm is proposed for affected operations. A case study illustrates that the proposed method can well accomplish the dynamic scheduling of VPSs in a self-adaptive manner.     

Adaptive production scheduling of virtual production systems using object-oriented Petri nets with changeable structure

Virtual Production Systems (VPSs) are logically constructed by organizing production resources belonging to one or more physical manufacturing systems. VPSs can enhance the agility of manufacturing systems. However, an effective scheduling approach is required to cope with disturbance and changes to these systems. An adaptive production scheduling method is proposed. Object-oriented Petri nets with changeable structure (OPNs-CS) formulate the scheduling problem of VPSs. To resolve resource constraints in a VPS, the OPNs-CS is modified by introducing limited token available time and by revising the enabling and firing rules. The artificial intelligent heuristic search (A*) algorithm is modified and applied to generate the optimal or near optimal schedule. When a VPS encounters any disturbance, an estimate of the effects of the disturbance can be estimated by simulation on the OPNs-CS model. If the scheduling target (completion time) is not affected, rescheduling is not required. Whenever there is a change to the VPS, the TOPNs-CS model is updated to refresh VPS schedule. A case study is presented to demonstrate the procedures for applying the proposed scheduling approach. The given case study shows that the proposed approach is capable of scheduling a VPS dynamically in response to disturbances and changes are involved.     

Deadlock-free scheduling in flexible manufacturing systems using Petri nets

This paper addresses the deadlock-free scheduling problem in Flexible Manufacturing Systems. An efficient deadlock-free scheduling algorithm was developed, using timed Petri nets, for a class of FMSs called Systems of Sequential Systems with Shared Resources (S 4 R). The algorithm generates a partial reachability graph to find the optimal or near-optimal deadlock-free schedule in terms of the firing sequence of the transitions of the Petri net model. The objective is to minimize the mean flow time (MFT). An efficient truncation technique, based on the siphon concept, has been developed and used to generate the minimum necessary portion of the reachability graph to be searched. It has been shown experimentally that the developed siphon truncation technique enhances the ability to develop deadlock-free schedules of systems with a high number of deadlocks, which cannot be achieved using standard Petri net scheduling approaches. It may be necessary, in some cases, to relax the optimality condition for large FMSs in order to make the search effort reasonable. Hence, a User Control Factor (UCF) was defined and used in the scheduling algorithm. The objective of using the UCF is to achieve an acceptable trade-off between the solution quality and the search effort. Its effect on the MFT and the CPU time has been investigated. Randomly generated examples are used for illustration and comparison. Although the effect of UCF did not affect the mean flow time, it was shown that increasing it reduces the search effort (CPU time) significantly.     

A comparison of sequencing rules in static and dynamic hybrid flow systems

It is well known that efficient scheduling of jobs is essential for improving the economics of production in manufacturing organizations. As a result, extensive research has been conducted on scheduling, especially in job shop and flow shop settings. In contrast, little research has been done on hybrid flow systems, even though they are found in many industries, including beer processing, glass container production, pertroleum refining, plastic-coated cable production, and fertilizer production. Furthermore, the few studies that have dealt with hybrid systems have been limited by the assumptions made about their operating environments. Therefore, we conducted a study that extends the previous work on hybrid systems in two significant ways: (1) it included financially oriented scheduling rules and a new, related performance measure; and (2) the new rules were compared with the existing ones in a large simulation experiment under both static and dynamic (generally encountered in practice) hybrid flow shop environments. To date such comparisons have been made only under static environments. The results show that the relative performances of the scheduling rules differ as the assumptions regarding the operating environment are changed.     

Performance-based dynamic scheduling model for flexible manufacturing systems

A performance-based dynamic scheduling model for random flexible manufacturing systems (FMSs) is presented. The model is built on the mathematical background of supervisory control theory of discrete event systems. The dynamic FMS scheduling is based on the optimization of desired performance measures. A control theory-based system representation is coupled with a goal programming-based multi-criteria dynamic scheduling algorithm. An effectiveness function, representing a performance index, is formulated to enumerate the possible outputs of future schedules. Short-term job scheduling and dispatching decisions are made based on the values obtained by optimizing the effectiveness function. Preventive actions are taken to reduce the difference between actual and desired target values. To analyse the real-time performance of the proposed model, a software environment that included various Visual Basic Application® modules, simulation package Arena®, and Microsoft Access® database was developed. The experimentation was conducted (a) to determine the optimum look-ahead horizons for the proposed model and (b) to compare the model with conventional scheduling decision rules. The results showed that the proposed model outperformed well-known priority rules for most of the common performance measures.     

Deadlock-free genetic scheduling for flexible manufacturing systems using Petri nets and deadlock controllers

In this paper, a new deadlock-free scheduling method based on genetic algorithm and Petri net models of flexible manufacturing systems is proposed. The optimisation criterion is to minimise the makespan. In the proposed genetic scheduling algorithm, a candidate schedule is represented by a chromosome that consists of two sections: route selection and operation sequence. With the support of a deadlock controller, a repairing algorithm is proposed to check the feasibility of each chromosome and fix infeasible chromosomes to feasible ones. A feasible chromosome can be easily decoded to a deadlock-free schedule, which is a sequence of transitions without deadlocks. Different kinds of crossover and mutation operations are performed on two sections of the chromosome, respectively, to improve the performance of the presented algorithm. Computational results show that the proposed algorithm can get better schedules. Furthermore, the proposed scheduling method provides a new approach to evaluate the performance of different deadlock controllers.     

Deadlock control of autonomous vehicle storage and retrieval systems via coloured timed Petri nets and digraph tools

This paper addresses the deadlock control problem for the autonomous vehicle storage and retrieval system (AVS/RS). For an AVS/RS with several autonomous vehicles running in bi-direction, deadlock control is one of the key issues in the implementation of AVS/RS. The cycle-deadlock is the main type of deadlock in AVS/RS. In the paper, the dynamic model of AVS/RS is investigated by using coloured timed Petri nets (CTPN). Based on the CTPN model, a route digraph is built to detect cycle-deadlock in AVS/RS with digraph tools; the necessary and sufficient conditions of deadlock-free are established. Moreover deadlock-free control policies are proposed, the critical state in deadlock free is also identified and FCFS policy is applied to solve it. Finally, a case study is given to validate the policies.     

Development of integrated production scheduling system for iron and steel works

The primary purpose of production scheduling at an integrated iron and steel works is to establish and execute the optimum production schedule that can improve both productivity and yield at each of the plants such as the steelmaking plants and rolling mills, while giving first consideration to the keeping of the date of delivery

However, it is by no means a simple matter to establish and control an integrated or consistent production, schedule covering about ten production processes for various products with an annual output of 6 million tons or more, or about 26 000 orders monthly

In our system-development efforts, therefore, we made the system under study simple and usable in practical applications, designed a scheduling simulator capable of policy selection, and thereby successfully developed an integrated production scheduling system centring around the scheduling simulator.     

A behavior based nonlinear multi‐agent framework using a hybrid approach

Abstract

In this paper, a novel design and implementation of a multi‐agent system via a hybrid approach is proposed. First of all, an autonomous agent is insured to be stable by employing the proposed local feedback control besides appropriate switching among well‐posed behaviors including obstacle avoidance, target approaching, wandering, manipulator grasping, etc. Next, a hybrid framework of the multi‐agent system (HMAS) is established for dealing with multi‐agent cooperative problems. The architecture of the inherent hierarchical control is designed consisting of two levels, where the first (lower) level mainly handles the continuous state describing the data acquired from various sensors, whereas the second (higher) level is responsible for providing a well performed supervisory control that can manipulate all available resources to successfully accomplish the underlying mission. In the Advanced Control Laboratory of the Department of Electrical Engineering at National Taiwan University, an actual wheeled mobile robot (WMR) has been developed, named The Treasure Hunter (TTH), which is able to hunt treasures in an unknown environment whereby the effectiveness of the proposed approach can be satisfactorily demonstrated.     

An energy-efficient scheduling and rescheduling method for production and logistics systems†

Scheduling can be defined as the allocation of available resources over time while optimising a set of criteria like early completion time of task, holding inventory, etc. The complexity of the scheduling problem, already known to be high, increases if dynamic events and disruptions are considered. In addition, in production and logistics, designers of scheduling systems must consider sustainability-related expectations. This paper presents an energy-efficient scheduling and rescheduling method (named Green Rescheduling Method, GRM). GRM aims at the solving of the dynamic scheduling problem under the condition of a certain level of routing flexibility enabling the reassignment of tasks to new resources. The key performance indicators integrated into the proposed GRM are effectiveness and efficiency-oriented. Applications concern the domains of production and logistics. In order to assess the proposed approach, experimentations have been made and results illustrate the applicability of GRM to build efficient and effective scheduling and rescheduling both for flexible manufacturing systems and inventory distribution systems in a physical internet network. A mathematical formulation for flexible job shop problem with energy consumption is also proposed using mixed Integer programming to evaluate the performance of the predictive part of GRM.     

Supervisory control and data acquisition for virtual enterprise

The new manufacturing paradigms, such as agile manufacture and lean production, are leading industrial countries towards the new generation of concurrent enterprises involving virtual enterprise architecture and concurrent engineering extended methodology. Continuing adaptation to the market can only be achieved efficiently if the planning and control processes are both optimized horizontally (Automatic Control Systems) and vertically (Management Control Systems). The desired improvement in performance and the realization of global enterprise objectives require a tight integration of the units of the enterprise. The close monitoring of the operational performance of various plants, manufacturing shop-floors/cells/machines, as well as their associated instrumentation and control is of increasing strategic importance. Failures can lead to increased costs and reduced product quality, consistency and production, and to plant shutdowns and increased environmental impact. There is a real need for advanced monitoring technologies to be applied, and their potential demonstrated, on complex industrial plants. The planning and scheduling of manufacturing systems integrated into virtual enterprise architectures requires the implementation of new General Master Production Planning and Scheduling techniques and Supervisory Control and Data Acquisition (SCADA) functions. This paper discusses some key issues on the SCADA-oriented open system for virtual enterprise architecture.     

经编机电子贾卡混合异构串行通信系统设计

针对传统经编机多板卡架构的电子贾卡控制系统存在的可靠性低、维护困难等问题,设计了一种面向工程应用、高度集成的新型嵌入式电子贾卡导纱针块(embedded electronic jacquard guide bar,EEJGB)。基于EEJGB,提出了一种兼顾通信可靠性和容错性的分布式混合异构串行通信架构,并对该通信架构进行了实时性分析。同时,为获取EEJGB的地址,提出了一种动态分配机制。为了验证该通信方法的有效性和可行性,以Modbus协议下的具体通信方法实例进行试验分析。分析结果表明:所提出的混合异构串行通信架构实时性高,在保证花型文件可靠传输的同时,极大地便利了EEJGB的故障定位、快速检修和分布式扩展,研究结果能够为新一代集成电子贾卡控制系统的设计提供有效的参考。     

Two-stage hybrid flow shop scheduling with preventive maintenance using multi-objective tabu search method

This paper investigates an integrated bi-objective optimisation problem with non-resumable jobs for production scheduling and preventive maintenance in a two-stage hybrid flow shop with one machine on the first stage and m identical parallel machines on the second stage. Sequence-dependent set-up times and preventive maintenance (PM) on the first stage machine are considered. The scheduling objectives are to minimise the unavailability of the first stage machine and to minimise the makespan simultaneously. To solve this integrated problem, three decisions have to be made: determine the processing sequence of jobs on the first stage machine, determine whether or not to perform PM activity just after each job, and specify the processing machine of each job on the second stage. Due to the complexity of the problem, a multi-objective tabu search (MOTS) method is adapted with the implementation details. The method generates non-dominated solutions with several parallel tabu lists and Pareto dominance concept. The performance of the method is compared with that of a well-known multi-objective genetic algorithm, in terms of standard multi-objective metrics. Computational results show that the proposed MOTS yields a better approximation.     

Guidelines for implementing robust supervisors in flexible manufacturing systems

Over the past several years, researchers have developed numerous control policies that assure deadlock-free operation for flexible manufacturing systems. Using this research base as a foundation, we have developed several supervisory policies that assure robust operation in the face of resource failure. Along with deadlock-free operation, these policies guarantee that failure of unreliable resources does not block production of part types not requiring failed resources. In our previous work, we developed two types of robust policies, those that ‘absorb’ all parts requiring failed resources into the buffer space of failure-dependent resources (resources that support only parts requiring failed resources), and those that ‘distribute’ parts requiring failed resources among the buffer space of shared resources (resources shared by parts requiring and parts not requiring failed resources). These two types of robust controllers assure different levels of robust system operation and impose very different operating dynamics on the system, thus affecting system performance in different ways. In this research, we use extensive simulation and experimentation on a highly complex and configurable system to develop guidelines for choosing the best robust supervisor based on manufacturing system characteristics and performance objectives. We validate these guidelines using seven randomly generated complex systems and find a better than 88% agreement.     

Book review of Global Strategic Management,by P. Lasserre,Palgrave Macmillan,Basingstoke, 2003, xx + 454 pp., £24.99, softcover (ISBN 0 333 79375 7)

This paper considers the simultaneous scheduling of material handling transporters (such as automatic guided vehicles or AGVs) and manufacturing equipment (such as machines and workcentres) in the production of complex asembled product. Given the shipping schedule for the end-items, the objective of the integrated problem is to minimize the cumulative lead time of the overall production schedule (i.e. total makespan) for on-time shipment, and to reduce material handling and inventory holding costs on the shop-floor. The problem of makespan minimization is formulated as a transportation integrated scheduling problem, which is NP-hard. For industrial size problems, an effective heuritsic is developed to simultaneouly schedule manufacturing and material handling operations by exploting the critical path of an integrated operation network. The performance of the proposed heuristic is evaluated via extensive numerical studies and compared with the traditional sequential scheduling approach. The superiority of the integrated heuristic is well documented.     

Ground resource optimization for navigation constellation based on satellite link scheduling

The Global Navigation Satellite System (GNSS) provides autonomous geospatial positioning and time synchronization services for civilian and military purposes. GNSS satellite links are used to transmit signals for constellation management and other applications. To minimize the number of stations required in participant ground-based management and reduce management costs in the GNSS network, this study solves the satellite link scheduling problem over the dynamic satellite network, including the hybrid and fast-varying inter-satellite link (ISL) working system. Firstly, the management problem is divided into two phases. Secondly, a two-level solving scheme is designed according to the characteristics of the scheduling problem. Finally, a performance analysis of different scenarios is conducted. The experimental results show that the hybrid ISL working system provides more effectively utilized data transmitting bandwidth of satellite links, thereby reducing the use of ground-based management resources. This study provides a technical reference for the management of future large-scale satellite networks.     

Modelling and analysis of wafer fabrication scheduling via generalized stochastic Petri net and simulated annealing

Some of the important characteristics of the semiconductor wafer fabrication factories are re-entrant process flows, a dynamic and uncertain environment, stringent production control requirements, etc. that pose a major challenge to the scheduling decisions in integrated circuit wafer fabrication process. Keeping in view the high capital investment and quick response to the market changes, it is essential for the integrated circuit fabrication process to exercise effective control on its production operations so that production resources can be employed in a flexible and efficient manner. The present research has focussed on the development of a generalized stochastic Petri net model that faithfully captures dynamic behaviours such as re-entrant processing, machine failures, loading and unloading, etc., pertaining to wafer fabrication. A simulated annealing-based scheduling strategy using mean cycle time and tardiness as performance measures was also developed to obtain an efficient and robust schedule for a known hard problem. Analysis of variance was applied to examine the interaction effects of various scheduling rules and to identify the main as well as the interaction effects of dispatching rules, dispatching rules and set-up rules, and set-up rules and batching rules. Paired t-tests were applied to assess the performance of rule combinations for lot and batch scheduling. The proposed simulated annealing-based solution methodology was tested on a well-known data set adopted from the literature and its performance reveals that simulated annealing-based scheduling rules work better than existing rules in terms of the two performance measures mean cycle time and tardiness.     

An energy-efficient two-stage hybrid flow shop scheduling problem in a glass production

Energy-efficient scheduling is highly necessary for energy-intensive industries, such as glass, mould or chemical production. Inspired by a real-world glass-ceramics production process, this paper investigates a bi-criteria energy-efficient two-stage hybrid flow shop scheduling problem, in which parallel machines with eligibility are at stage 1 and a batch machine is at stage 2. The performance measures considered are makespan and total energy consumption. Time-of-use (TOU) electricity prices and different states of machines (working, idle and turnoff) are integrated. To tackle this problem, a mixed integer programming (MIP) is formulated, based on which an augmented ε-constraint (AUGMECON) method is adopted to obtain the exact Pareto front. A problem-tailored constructive heuristic method with local search strategy, a bi-objective tabu search algorithm and a bi-objective ant colony optimisation algorithm are developed to deal with medium- and large-scale problems. Extensive computational experiments are conducted, and a real-world case is solved. The results show effectiveness of the proposed methods, in particular the bi-objective tabu search.     

An effective heuristic for adaptive control of job sequences subject to variation in processing times

Variation in sequential task processing times is common in manufacturing systems. This type of disturbance challenges most scheduling methods since they cannot fundamentally change job sequences to adaptively control production performance as jobs enter the system because actual processing times, are not known in advance. Some research literature indicates that simple rules are more suitable than algorithmic scheduling methods for adaptive control. In this work, a ‘state space – average processing time’ (SS-APT) heuristic is proposed and compared to four most commonly used scheduling rules and two well-established heuristics based on Taillard’s benchmarks. It is shown that the adaptive control is made possible under variation in processing times given the flexibility and strong performance of the SS-APT heuristic, especially for work-in-process inventory control.