Jobshop lot streaming with routing flexibility,sequence-dependent setups,machine release dates and lag time

Lot streaming is a technique of splitting production lots into smaller sublots in a multi-stage manufacturing system so that operations of a given lot can overlap. This technique can reduce the manufacturing makespan and is an effective tool in time-based manufacturing. Research on lot streaming models and solution procedures for flexible jobshops has been limited. The flexible jobshop scheduling problem is an extension of the classical jobshop scheduling problem by allowing an operation to be assigned to one of a set of eligible machines during scheduling. In this paper we develop a lot streaming model for a flexible jobshop environment. The model considers several pragmatic issues such as sequence-dependent setup times, the attached or detached nature of the setups, the machine release date and the lag time. In order to solve the developed model efficiently, an island-model parallel genetic algorithm is proposed. Numerical examples are presented to demonstrate the features of the proposed model and compare the computational performance of the parallel genetic algorithm with the sequential algorithm. The results are very encouraging.     

An examination of routeing flexibility for small batch assembly of printed circuit boards

In this paper, we examine and quantify the effects of introducing new processing flexibility in the rapidly changing environment of printed circuit board (PCB) assembly. Specifically, we perform experiments designed to establish the benefits and determine the limitations associated with the introduction of routeing flexibility. We examine system behaviour as batch sizes are reduced in an environment characterized by moderate set-up requirements. We further demonstrate that the performance of flexible routeing policies in this environment is adversely affected by larger batch sizes and that the introduction of routeing flexibility leads to improved system performance in small batch assembly.     

Launching and dispatching strategies for multi-criteria control of closed manufacturing systems with flexible routeing capability

In this paper, we study the problems of launching and dispatching of parts in closed manufacturing systems with flexible routeing. For the manufacturing systems being operated against multiple performance criteria, we postulate that controlling different aspects of the operational control strategy to meet one single performance criterion would improve overall system performance. It is suggested that to achieve production rates, launching rules be utilized and to affect flowtime, dispatching rules be manipulated. Also, for measurement of routeing flexibility, an entropic measure of flexibility is refined. The entropy-based rule is then compared with the dispatching rules commonly used in the industry. Control strategies are developed for a test system and it is shown that a hierarchical control strategy works best when multiple performance criteria are of interest.     

Effects of loading and routeing decisions on performance of flexible manufacturing systems

Research has found that while flexibility is purported to be a prime advantage of flexible manufacturing systems (FMS), it has not yet become a major competitive priority for American and European manufacturers. Moreover, many installed systems either are not very flexible or do not use the available flexibility to the best advantages. We suspect that inappropriate application of the conventional production management concepts to FMS is one of the major factors that hinders current FMSs from capturing their key advantage: flexibility. This paper takes a first step to examine why the conventional job shop loading and fixed routeing concepts fail to capture the flexibility of FMS. Once problems are identified we suggest ways to exploit the FMS flexibility. We further conduct an experiment to investigate FMS performance under different manufacturing policies and operating conditions. The results indicate that the performance of an FMS greatly diminishes when the conventional job shop loading and fixed routeing concepts are applied. This is because the inherent flexibility of the FMS is not fully utilized. Moreover, the operating conditions such as tooling duplication levels and operation processing time variation could also significantly affect the FMS performance.     

Part type selection,machine loading and part type volume determination problems in FMS planning

The solution to subproblems of FMS planning problems require an integrated approach. The mathematical programming approaches, which are often followed, are not suitable for large problems. In this paper, we have proposed a three stage approach to solving part type selection, machine loading and part type volume determination problems. In contrast to the usual approach of maximizing the part types in each batch (or minimizing the number of batches), we have attempted to maximize the routeing flexibility of the batches. A heuristic has been proposed for the part type selection problem and simple mathematical programs for the other two problems. The illustrative examples show that by improving the routeing flexibility of the batches the overall system performance has improved.     

Design of a tool management system in a flexible cell

In this work we describe the design of a tool management system of a flexible manufacturing facility operating in the avionics components industry, The design included several modifications to the existing system. While previously the tool handling devices were used only to perform machine setup, the modifications allowed the tools to be shared among machines. This allowed a full exploitation of the flexibility of the system. In the work we thoroughly report on the procedures implemented for the determination of tools to be duplicated, for part routeing and scheduling, and for tool movements synchronization.     

Tabu search for the job-shop scheduling problem with multi-purpose machines

In this paper we study the following generalization of the job-shop scheduling problem. Each operation can be performed by one machine out of a set of machines given for this operation. The processing time does not depend on the machine which has been chosen for processing the operation. This problem arises in the area of flexible manufacturing. As a generalization of the jobshop problem it belongs to the hardest problems in combinatorial optimization. We show that an application of tabu search techniques to this problem yields excellent results for benchmark problems.Supported by Deutsche Forschungsgemeinschaft, Project JoP-TAG     

An algorithm for sub-optimal routeing in series-parallel queueing networks

The optimal routeing problem of maximizing system throughput in series-parallel networks with finite buffers is studied in this paper. The problem is extremely difficult to solve since closed form expressions are not easily constructed for throughput in finite networks. A piece-wise linear upper bound on the throughput of a tandem network is used to develop a throughput approximation in seriesparallel networks. Based on this approximation we are able to specify a suboptimal range for routeing probabilities at each junction in the network as a function of the arrival rate to this junction. We also specify a unique value for the routeing probability at each junction, independent of the arrival rate to that junction. We then construct an O(N) algorithm to analyse general series-parallel networks with more than one junction and specify the sub-optimal routeing probabilities at each junction.     

Logical reconfiguration of reconfigurable manufacturing systems with stream of variations modelling: a stochastic two-stage programming and shortest path model

Designing flexible manufacturing systems in general, and flexible material handling system in particular, is a complex problem, typically approached through several stages. Here the focus is on the conceptual design stage during which valid approximation-based methods are needed. The segmented flow topology (SFT) AGV systems were developed to facilitate control of complex automated material handling systems. This paper introduces a decomposition method, directly derived from timed Petri nets (TPN) theories, to calculate the expected utilization of AGVs (as servers of SFT systems) and to derive simple operational decision rules leading to maximum system productivity at steady state, for a given deterministic routeing of discrete material through the manufacturing system.     

Investigations into the impact of flexibility on manufacturing performance

This paper provides investigative insights into the impact of routeing flexibility, machine flexibility, and product-mix flexibility on the performance of a manufacturing plant. The study employs simulation modelling as the primary tool. The facility modelled is an automobile engine assembly plant consisting of a FMS (flexible manufacturing systems), job shop, and assembly line. A variety of experiments, with the FMS exhibiting one or more of the above three flexibilities at different levels, were simulated on the model. In each experiment the manufacturing performance as given by flow time and work-in-process inventory was tracked. The experiments focused first on the FMS itself, and then on the entire plant. Measures for the three flexibilities are introduced. The simulation results are analysed in detail. The results indicate significant performance benefits in context of the FMS, but little in context of the overall plant     

A Multifactor Priority Rule for Jobshop Scheduling Using Computer Search

Priority rules are widely used in jobshop scheduling to determine the sequence in which jobs are to be processed. The research in this area has been directed at developing generally applicable priority rules. This paper presents a method for determining an effective priority rule specific to the jobshop scheduling problem to be solved. First, a generalized objective function is formulated which is the sum of costs of tardiness, carrying in-process inventory and machine idleness. Second, a multifactor priority rule is developed which is a weighted average of four factors used in simple priority rules. Third, a method is presented for using a computer search technique to determine the best weights to use in the priority rule. Finally, a computer simulation for testing this approach versus using other priority rules is described and the experimental results are reported.     

The periodic routeing of a flexible manufacturing system with centralized in-process inventory flows

We consider a flexible manufacturing system consisting of one unlimited central buffer and n workstations each having a limited local buffer. The in-process inventory is centralized through the central buffer. General independent random processing times are assumed at each station. The system is reviewed periodically. We address the routeing control problem, where the routeings of jobs from the central buffer to each station are to be determined periodically to minimize the in-process inventory costs. A dynamic programming model is developed for the determination of the optimal routeings. The computational formulae are derived, and a solution approach is established. The computational results for a real flexible manufacturing system are reported.     

Precedence constrained TSP applied to circuit board assembly and no wait flowshop

The travelling salesman problem formulation is extended to allow precedence constraints between cities. A method is proposed for finding good inexpensive solutions to this problem with results illustrated by several scheduling applications: circuit board assembly, courier routeing and the no wait flowshop scheduling problem.     

Intelligent dispatching for flexible manufacturing

A decision rule for real-time dispatching of parts, each of which may have alternative processing possibilities, has been developed and tested in a simulated flexible manufacturing system. A part, upon completion of an operation, is not routed to a specific machine, but is, in effect, sent to a general queue. Thus, a machine has a global option for choosing parts which in turn may be processed on alternative machines. For effective use of the system's routeing flexibility under these circumstances, the machine needs an intelligent part-selection strategy (rather than shallow heuristics represented by the conventional dispatching rules) that takes into account the current state and trends of the system. The proposed intelligent reasoning procedure has been found to achieve better shop performance than some of the popular dispatching rules, the improved performance being due to the ability to respond to changing circumstances.     

Effect of manufacturing system constructs on pick-up and drop-off strategies of multiple-load AGVs

This research investigates the interaction between manufacturing system constructs and the operation strategies in a multiple-load Automated Guided Vehicle System (AGVS) when AGVs in a system can carry two or more loads. The load pick-up problem arises when an AGV stops at a pick-up queue and has to decide which part(s) in the queue should be picked up. Since an AGV can carry multiple loads, a drop-off rule is then needed to determine the next stop for the AGV to deliver one or more loads. Several real-time composite heuristic rules for selecting load and determining the next stop are proposed and evaluated in two manufacturing system constructs: the jobshop and the flexible manufacturing system (FMS). A number of simulation models are developed to obtain statistics on various performance measures of the two system constructs under different experimental conditions. The simulation results reveal that the pick-up rules affect the system more than the drop-off rules. In general, rules to avoid starving and blocking in workstations perform better than the rules for shortest distance in throughput. However, the rules perform differently in jobshop and FMS based on other performance measures, indicating an interaction between system constructs and load selection strategies. The difference in rule performance within the same construct is also affected by several AGVS design parameters. Overall our study suggests that no load pick-up rule is always a champion, and the design of an efficient multiple-load AGVS must consider all issues in a global fashion.     

A memetic algorithm for multi-objective flexible job-shop problem with worker flexibility

In existing scheduling models, the flexible job-shop scheduling problem mainly considers machine flexibility. However, human factor is also an important element existing in real production that is often neglected theoretically. In this paper, we originally probe into a multi-objective flexible job-shop scheduling problem with worker flexibility (MO-FJSPW). A non-linear integer programming model is presented for the problem. Correspondingly, a memetic algorithm (MA) is designed to solve the proposed MO-FJSPW whose objective is to minimise the maximum completion time, the maximum workload of machines and the total workload of all machines. A well-designed chromosome encoding/decoding method is proposed and the adaptive genetic operators are selected by experimental studies. An elimination process is executed to eliminate the repeated individuals in population. Moreover, a local search is incorporated into the non-dominated sorting genetic algorithm II. In experimental phase, the crossover operator and elimination operator in MA are examined firstly. Afterwards, some extensive comparisons are carried out between MA and some other multi-objective algorithms. The simulation results show that the MA performs better for the proposed MO-FJSPW than other algorithms.     

Dispatching rules for scheduling in assembly jobshops - Part 1

Research on jobshop scheduling has tended to concentrate on the development of dispatching rules for jobs that are independent, i.e. single-component jobs. However, in real-life situations, many jobs involve assembly operations that require scheduling of multiple components through the jobshop where both serial and parallel operations take place. In this two-part paper, we consider the problem of scheduling in assembly jobshops, i.e. jobshops that manufacture multi-level assembly jobs. The development of new and efficient dispatching rules with a view to address various measures of performance related to flowtime and staging delay of jobs is first undertaken. A new concept, called 'operation synchronization date' is introduced and made use of in the new dispatching rules. The best existing dispatching rules and the proposed dispatching rules are relatively evaluated by an exhaustive simulation study. The results indicate that the proposed rules emerge to be superior to the existing ones for most measures of performance.     

Dynamic routing and the performance of automated manufacturing cells

There has been a considerable amount of research done on the “cell formation” problem, in which machining cells are designed to process a family of components. More recently, it has been suggested that machining cells should be designed so that they take advantage of the flexibility for processing parts that have alternate, or multiple machine routing possibilities. It is argued that such flexibility will improve machine utilization as well as other measures of cell performance and may reduce the need for centralized cell loading and scheduling algorithms. Unfortunately, if the cell is automated, routing flexibility requirements can create a complex control problem for the cell controller. In this paper we implement a cell controller designed to handle the requirements of the flexible routing of parts and compare the performance of the cell to the case in which each part has only one routing. We find that significant improvements occur when the cell design is capable of processing parts with flexible routings.     

A hybrid artificial bee colony algorithm for flexible job shop scheduling with worker flexibility

The traditional flexible job shop scheduling problem (FJSP) considers machine flexibility but not worker flexibility. Given the influence and potential of human factors in improving production efficiency and decreasing the cost in practical production systems, we propose a mathematical model of an extended FJSP with worker flexibility (FJSPW). A hybrid artificial bee colony algorithm (HABCA) is presented to solve the proposed FJSPW. For the HABCA, effective encoding, decoding, crossover and mutation operators are designed, and a new effective local search method is developed to improve the speed and exploitation ability of the algorithm. The Taguchi method of Design of Experiments is used to obtain the best combination of key parameters of the HABCA. Extensive computational experiments carried out to compare the HABCA with some well-performing algorithms from the literature confirm that the proposed HABCA is more effective than these algorithms, especially on large-scale FJSPW instances.     

A learning-based methodology for dynamic scheduling in distributed manufacturing systems

To enhance productivity in a distributed manufacturing system under hierarchical control, we develop a framework of dynamic scheduling scheme that explores routeing flexibility and handles uncertainties. We propose a learning-based methodology to extract scheduling knowledge for dispatching parts to machines. The proposed methodology includes three modules: discrete-event simulation, instance generation, and incremental induction. First, a sophisticated simulation module is developed to implement a dynamic scheduling scheme, to generate training examples, and to evaluate the methodology. Second, the search for training examples (good schedules) is successfully fulfilled by the genetic algorithm. Finally, we propose a tolerance-based learning algorithm that does not only acquire general scheduling rules from the training examples, but also adapts to any newly observed examples and thus facilitates knowledge modification. The experimental results show that the dynamic scheduling scheme significantly outperforms the static scheduling scheme with a single dispatching rule in a distributed manufacturing system.