The part mix and routing mix problem in FMS: a coupling between an LP model and a closed queueing network

In the near future many companies will face the problem of the optimal use of newly installed manufacturing technology (e.g. a flexible manufacturing system or FMS). Very often this will involve decisions on what parts to produce using the new system (the part mix problem) and how to produce these parts (the routing mix problem). We show that traditional operational research tools such as linear programming and queueing network theory are well suited to tackle these problems. In particular, LP models are combined with queueing network models in an iterative procedure. As such the strengths of both techniques can be exploited in making optimal use of the part mix and routing mix flexibility of the FMS.     

Incorporating dynamism in traditional machine loading problem: an AI-based optimisation approach

Machine breakdowns have been recognised in flexible manufacturing systems (FMS) as the most undesirable characteristic adversely affecting the overall efficiency. In order to ameliorate product quality and productivity of FMS, it is necessary to analyse, as well as to minimise the effect of breakdowns on the objective measures of various decision problems. This paper addresses the machine loading problem of FMS with a view to maximise the throughput and minimise the system unbalance and makespan. Moreover, insufficient work has been done in the domain of machine loading problem that considers effect of breakdowns. This motivation resulted in a potential model in this paper that minimises the effect of breakdowns so that profitability can be augmented. The present work employs an on-line machine monitoring scheme and an off-line machine monitoring scheme in conjunction with reloading of part types to cope with the breakdowns. The proposed model bears similarity with the dynamic environment of FMS, hence, termed as the dynamic machine loading problem. Furthermore, to examine the effectiveness of the proposed model, results for throughput, system unbalance and makespan on different dataset from previous literature has been investigated with application of intelligence techniques such as genetic algorithms (GA), simulated annealing (SA) and artificial immune systems (AIS). The results incurred under breakdowns validate the robustness of the developed model for dynamic ambient of FMS.     

A mathematical programming model for reconfiguration of flexible manufacturing cells

In flexible manufacturing cells, changes in demand size, product mix, part variety, existing routings and set-up/operation times may require reconfiguration of the cells. In this study, an approach is developed to decide when and how such a reconfiguration should be carried out for existing cells. This study considers reconfiguration in terms of changing part routings, adding a new machine type in a cell, duplicating an existing machine type, removing an existing machine from a cell and transferring a machine to another cell. The study also shows the total number of tools of each type on each machine located in each cell after reconfiguration. To make the optimal reconfiguration decisions, a mathematical programming model to minimize the total reconfiguration cost is developed. The developed model considers the lower and upper bounds on machine utilizations and the time limits on machine cycle times to decide when to reconfigure the system.     

Flexible manufacturing system structural control and the Neighborhood Policy,part 2. Generalization,optimization, and efficiency

In the first of this pair of papers, the Neighborhood Policy was shown to be a correct and scalable Structural Control Policy (SCP). Operating constraints that guarantee deadlock-free flexible manufacturing system (FMS) operation are generated based on machine capacity. For some systems these constraints appear to be quite conservative. This paper generalizes the Neighborhood Policy so that many different SCPs can be generated for the same FMS configuration. A method of finding permissive neighborhood systems is then developed. Finally, SCP efficiency is defined and investigated for Capacity-Based and Optimal Neighborhood Policies.     

On the performance of hybrid multi-cell flexible manufacturing systems

Industrial experience has shown that it is virtually impossible to implement a large-scale flexible manufacturing system (FMS) without using the group technology manufacturing concept. However, grouping machines into product cells can limit the FMS flexibility. Thus when the production cells are not completely disjoint, problems under multi-cell flexible manufacturing systems (MCFMS) can be caused by changes in job mix and demand which lead to a workload imbalance both between cells and between machine centres within the same cell. The problems can be mitigated and shop performance improved by transferring workloads from a congested machine centre in one cell to an alternative, less congested machine centre in another cell. Such inter-cell workload transfer results in a hybrid MCFMS which is a cross between a parts similarity-based MCFMS and a process similarity-based MCFMS. Results of a simulation study carried out by the author show that inter-cell workload transfer is very effective in improving shop performance. This paper briefly describes the simulation study and discusses the implications of its results for the design and operation of FMSs. The operational viability, and economic feasibility of hybrid MCFMSs are also discussed in the paper.     

Material requirements planning with flexible bills-of-material

In conventional Material Requirements Planning (MRP), a Bills-of-Materials (BOM) for products is fixed. If time or quantity as stated in the Master Production Schedule (MPS) is not flexible for the final product, flexible BOM may be introduced to compensate for the inflexibility in the MPS. This paper addresses situations where a flexible BOM could be used to deal with unexpected shortages when using MRP to plan for requirements of dependent demand items. The requirements stated in the MPS are met in a timely manner by allowing the substitution of items for one another in the case of a shortage. A linear programming (LP) formulation is provided to help deal, if possible, with a shortage using the flexibility in the BOM. The LP model identifies a ‘mix’ of lower-level items that satisfy both the reality of shortages and ensure as small a deviation from the default BOM as possible. A detailed example in the food production environment is presented to explain how the flexible BOM concept may be applied.     

Scheduling of machines and automated guided vehicles in FMS using differential evolution

This paper addresses the problem of simultaneous scheduling of machines and two identical automated guided vehicles (AGVs) in a flexible manufacturing system (FMS). For solving this problem, a new meta-heuristic differential evolution (DE) algorithm is proposed. The problem consists of two interrelated problems, scheduling of machines and scheduling of AGVs. A simultaneous scheduling of these, in order to minimise the makespan will result in a FMS being able to complete all the jobs assigned to it at the earliest time possible, thus saving resources. An increase in the performance of the FMS under consideration would be expected as a result of making the scheduling of AGVs as an integral part of the overall scheduling activity. The algorithm is tested by using problems generated by various researchers and the makespan obtained by the algorithm is compared with that obtained by other researchers and analysed.     

Managing flexible manufacturing technology: Must parts in an FMS always move in a job-shop manner?

The literature typically assumes that an FMS consists of a number of machines of different processing capability. Furthermore, in view of the inherent flexibility of an FMS, many researchers believe that 'flexible' implies that a wide variety of parts can be, and should be, processed simultaneously in an FMS. To do otherwise will inevitably mean some machines are idle and hence the FMS may become a tremendous waste. This paper is an attempt to study this issue. Unlike a job shop, which is typically an eclectic collection of machines of different process capabilities, most flexible manufacturing systems consist of only one or two types of versatile programmable machines. We contend that the FMS machines are analogous to the multi-skilled workers in lean production. In lean production, workers work in teams. It is common for each team to work on one job at a time, from start to finish. Jobs are not passed around from worker to worker. Likewise, machines in an FMS can be assigned into 'teams', where each 'team' is dedicated to process a single part type (or family) at a time. Parts do not necessarily have to move from machine to machine in a job shop manner.     

An object-oriented knowledge representation for hierarchical real-time control of flexible manufacturing

In this paper we demonstrate how a knowledge base can be constructed and used for real-time control of tool loading in a flexible manufacturing system (FMS). A procedure for dynamic tool loading is delineated to support variable production requirements expressed as a master production schedule (MPS). The main emphasis of this work is to propose a framework for real-time control to provide insights into the use of object-oriented structures for representing FMS entities.     

Design of an FMS decision support system

Flexible manufacturing system (FMS) is an integrated system consisting of computer numerical control machine tools and automated material handling system controlled by an overall control computer system. The FMS design is broken down into strategic, tactical and operational level designs. This research is concerned with the development of a decision support system for the design of FMS (FMSDDS. Simulation is used as a primary analysis tool, making the DSS capable of solving problems at all three levels. The decision making ability is provided by a multi-attribute utility model which accounts for both quantitative and qualitative factors that affect a decision. The FMSDSS is implemented using three routines: input, analysis, and output. The input routine helps the user to select feasible FMS configurations interactively. The analysis routine consists of a generalized FMS simulation model. This routine analyses the FMS alternatives selected and provides the information required for the output analysis. The qualitative and quantitative measures of performance that have to be considered for decision making are handled by the output routine. It also combines performance measures of different units such as time and cost. The DSS is modular and hence future enhancements can be readily added.     

Development of a simulation-based optimisation for controlling operation allocation and material handling equipment selection in FMS

Flexible manufacturing system (FMS) is described as a set of computerised numerical controlled machines, input–output buffers interconnected by automated material handling devices. This paper develops a bi-objective operation allocation and material handling equipment selection problem in FMS with the aim of minimising the machine operation, material handling and machine setup costs and maximising the machine utilisation. The proposed model is solved by a modified chaotic ant swarm simulation based optimisation (CAS²O) while applying pre-selection and discrete recombination operators is surveyed a capable method to simulate different experiments of FMS problems. A test problem is selected from the literature to evaluate the performance of the proposed approach. The results validate the effectiveness of the proposed method to solve the FMS scheduling problem.     

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.     

Solving machine loading problems in a flexible manufacturing system using a genetic algorithm based heuristic approach

The machine-loading problem of a flexible manufacturing system (FMS) has been recognized as one of the most important planning problems. In this research, a Genetic Algorithm (GA) based heuristic is proposed to solve the machine loading problem of a random type FMS. The objective of the loading problems is to minimize the system unbalance and maximize the throughput, satisfying the technological constraints such as availability of machining time, and tool slots. The proposed GA-based heuristic determines the part type sequence and the operation-machine allocation that guarantee the optimal solution to the problem, rather than using fixed predetermined part sequencing rules. The efficiency of the proposed heuristic has been tested on ten sample problems and the results obtained have been compared with those of existing methods.     

FMS machine loading: A simulated annealing approach

In this paper the problem of FMS machine loading is considered with the objective of minimizing the system imbalance using a simulated annealing (SA) approach. New job sequences are generated with a proposed perturbation scheme named the 'modified insertion scheme' (MIS). These sequences are used in the proposed simulated annealing algorithm to arrive at a near global optimum solution. A new approach for temperature variation in the SA algorithm is also suggested in which temperature is assumed to be parabolic. The SA algorithm using the proposed MIS and the assumed temperature variation proved to be giving substantial improvement in system imbalance as against conventional sequences.     

Modelling of flexible manufacturing system: a review

A flexible manufacturing system (FMS) due to its ability of being flexible in nature is concerned with automatic production of different parts in medium range. In short, it can be regarded as an automated manufacturing system. In this paper, an insight on previous work in the area of FMS modelling has been provided with an overview of research and development for better understanding of FMS. It serves as a medium for investigation of work that are accomplished by using different modelling techniques in FMS like mathematical, artificial intelligence, hierarchical, multi criteria decision-making method, Petri Nets and simulation. This paper will help researchers who are keen to do research in the area of FMS modelling, by highlighting contribution of available techniques in the field of FMS. It will also help them in deciding which modelling techniques can be used for a given problem. At last, comparison of different parameters considered in the recent papers of modelling FMS has been provided in the form of Table, along with a clear vision related to those works that still need to be investigated.     

Examining the use of dedicated and general purpose pallets in a dedicated flexible manufacturing system

This research describes one example of how the failure to understand the relationships between the flexibility associated with all resources within an FMS can be critical to overall performance. The need for such understanding is clearly spelled out by Jaikumar (1986). This research illustrates that even in situations where the demands placed upon the system are very well defined, tooling resources, such as pallets, may constrain overall system flexibility and subsequent system performance. In this paper, we simulate the operational performance of an existing FMS designed to manufacture a relatively small set of agricultural equipment components (only eight part types) over a known planning horizon using general purpose pallets and dedicated pallets. The simulation model is run under experimental conditions that include levels of: demand mix variability, number of each type pallet available to the system, and incremental loading time and scrap rate when general purpose pallets are used. In most cases, the results indicate a significant increase in system performance when using general purpose pallets. In general, while system performance decreases as the level of demand mix variability increases, relatively higher throughput is obtained using general purpose pallets except where the assumed incremental loading times and scrap rates associated with assembling the pallets are highest. System performance also improves as additional pallets are made available. In addition, overall system investment is impacted as fewer general purpose pallets are required to achieve a given level of performance compared to the use or dedicated pallets. As the overall system investment and scheduling restrictions associated with dedicated pallets would be expected to increase with the number of part types made in the system, the results found in this analysis for a dedicated FMS producing a small number of parts on a regular basis form a relative ‘lower bound’ on the scheduling and investment benefits of using general purpose pallets.     

Performance evaluation of flexible manufacturing systems with blocking

Analytical approximations for the performance of flexible manufacturing systems (FMS) with blocking of machines due to limited local buffers are presented. The approximations are based on a detailed analysis of FMS configurations used in industry. The method proposed uses informations generated by applying the classical closed queueing network (CQN) model to the FMS. The approximations developed are tested against simulation models for a wide variety of FMS configurations. The results presented show that the approximations are very good.     

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     

Experimental investigation of FMS machine and AGV scheduling rules against the mean flow-time criterion

Although a significant amount of research has been carried out in the scheduling of flexible manufacturing systems (FMSs), it has generally been focused on developing intelligent scheduling systems. Most of these systems use simple scheduling rules as a part of their decision process. While these scheduling rules have been investigated extensively for a job shop environment, there is little guidance in the literature as to their performance in an FMS environment. This paper attempts to investigate the performances of machine and AGV scheduling rules against the mean flow-time criterion. The scheduling rules are tested under a variety of experimental conditions by using an FMS simulation model.     

A methodology for designing flexible cellular manufacturing systems

Cell formation in cellular manufacturing deals with the identification of machines that can be grouped to create manufacturing cells and the identification of part families to be processed within each cell. Dynamic and random variations in part demands can negatively impact cell performance by creating unstable machine utilizations. The purpose of this paper is to introduce and illustrate an interactive cell formation method that can be used to design 'flexible' cells. Flexibility in this context refers to routing flexibility (i.e., the ability for the cellular system to process parts within multiple cells) and demand flexibility (i.e., the ability of the cell system to respond quickly to changes in part demand and part mix). Through an experimental analysis using multiple data sets, we also validate the procedure and provide guidelines for parameter settings depending upon the type of flexibility of interest to the user. Finally, trade-offs and interdependences between alternative types of flexibility in the context of cellular systems are illustrated.