Priority-based tool allocation in a flexible manufacturing system

The tool allocation problem in a flexible manufacturing system generally aims at (1) maximizing throughput (2) minimizing machining cost (3) minimizing system imbalance. This paper presents a heuristic approach of loading a set of tools to the different machining centres in the case of variable machining time. Concepts of fuzzy set theory to determine threshold machining time and a potency index (PI) to prioritize parts are used to solve the problem.     

A loading and dispatching problem in a random flexible manufacturing system

A scheduling problem in a flexible manufacturing system (FMS) is considered to be a composite of two interdependent tasks: loading and sequencing. Formulations are presented for the loading problem with two objectives:

(i) minimization of the system workload unbalance, and

(ii) minimization of system unbalance and the number of late jobs;

including constraints such as the number of tools slots with duplications, unique job routing, nonsplitting of jobs and machine capacity. For both the objectives, heuristic methods are developed and performance is compared with the exact mixed integer programming solutions. A simulation model is developed for investigating the system performance for the problem of minimizing the system unbalance using heuristic and sequential loading methods in conjunction with four—FIFO, SPT, LPT and MOPR—dispatching rules.     

Fuzzy goal-programming model with an artificial immune system (AIS) approach for a machine tool selection and operation allocation problem in a flexible manufacturing system

Some of the important planning problems that need realistic modelling and a quicker solution, especially in automated manufacturing systems, have recently assumed greater significance. In real-life industrial applications, the existing models considering deterministic situations fail as the true language adopted by foremen and technicians are fuzzy in nature. Thus, to map the situation on the shop floor to arrive at a real-time solution of this kind of tactical planning problem, it is essential to adopt fuzzy-based multi-objective goals so as to express the target desired by the management of business enterprises. This paper presents a fuzzy goal-programming approach to model the machine tool selection and operation allocation problem of flexible manufacturing systems. The model is optimized using an approach based on artificial immune systems and the results of the computational experiments are reported.     

A reallocation-based heuristic to solve a machine loading problem with material handling constraint in a flexible manufacturing system

In this research, a comprehensive heuristic solution is evolved to include all the three segments of a machine loading problem of flexible manufacturing systems. These are part type sequence determination, operation allocation on machines and reallocation of part types. The machine loading problem has been formulated keeping in view two well-known objective functions, namely minimization of system unbalance and maximization of throughput. In addition to constraints related to machine time and tool slots availability, this research considers one more constraint related to material handling, i.e. number of AGVs available in the system. The part type sequence determination has been carried out by evaluating the contribution of part type to characteristics such as batch size, total processing time, and the AGV movement. Decisions pertaining to operation allocation are taken based on the enumeration of priority index. An iterative reallocation procedure has been devised to ensure minimum positive system unbalance and maximum throughput. A test problem is simulated to represent the real shop floor environment and the same has been solved using various steps of the proposed algorithm. Extensive computational experiments have been carried out to assess the performance of the proposed heuristic and validate its relevance to solve the real shop floor problems.     

The tool transporter movements problem in flexible manufacturing systems

We consider a job sequencing and tool transporter movements problem on a single flexible machine with limited tool magazine capacity. A tool transporter having limited capacity is used in transporting the tools between the machine and tool crib area. Our aim is to minimize the number of the tool transporter movements. We present several lower and upper bounds, propose a Branch-and-Bound algorithm and a Beam Search procedure, and report results from a computational experiment. We find that optimal solutions can be quickly obtained for medium-sized instances with 25 jobs and 25 tools. For large-sized problem instances, Beam Search provides high quality solutions very quickly. Finally, we address the problem of minimizing the total flow time.     

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.     

Shop floor control and tool loading policies in flexible manufacturing systems

We develop a classification scheme and taxonomy of operating decisions in flexible manufacturing systems (FMS). The taxonomy is used to identify a promising research area termed General FMSs (GFMS), where very little academic work has been reported to date in the prior literature. A decision framework for the development of tool loading and shop floor control policies in GFMS is also presented, and used to highlight specific future research directions. Strategic justification for developing operating policies for the GFMS classification is also provided.     

Intelligent decision support system for the adaptive control of a flexible manufacturing system with machine and tool flexibility

This paper describes an intelligent decision support system (IDSS) for real time control of a flexible manufacturing system (FMS). The controller is capable of classifying symptoms in developing the control policies on FMSs with flexibility in operation assignment and scheduling of multi-purpose machining centres which have different tools with their own efficiency. The proposed system is implemented by coupling of rule-based IDSS, simulation block and centralised simulation optimiser for elicitation of shop floor control knowledge. This posteriori adaptive controller uses a new bilateral mechanism in simulation optimiser block for offline training of IDSS based on multi-performance criteria simulation optimisation. The proposed intelligent controller receives online information of the FMS current state and trigger appropriate control rule within real-time simulation data exchange. Finally the FMS intelligent controller is validated by a benchmark test problem. Application of this adaptive controller showed that it could be an effective approach for real time control of various flexible manufacturing systems.     

Some solution methodologies for loading problems in a flexible manufacturing system

The loading problem in a flexible manufacturing system (FMS) is viewed as selecting a subset of jobs from the job pool and allocating jobs among machines. A two-stage branch and backtrack procedure is developed with the objective of maximizing the assigned workload. Heuristic procedures are also developed with a bicriterion objective of minimizing the workload imbalance and maximizing the throughput for critical resources such as the number of tool slots on machines and the number of working hours in a scheduling period. The case of machine-dependent processing times is also dealt with. An illustrative numerical example accompanies each procedure.     

Joint consideration of grouping and loading problems in a flexible manufacturing system

The combined problem of grouping and loading in a flexible manufacturing system is formulated as a multistage multiobjective optimization model. The min-max approach to multiobjective optimization is used to obtain a compromise solution. The application of the model is illustrated by an example.     

Minimization of tool switches for a flexible manufacturing machine with slot assignment of different tool sizes

The problem addressed in this paper is the tool switching problem for an automated manufacturing environment, when each tool may occupy more than one slot of the tool magazine. A machine processes parts automatically by using a limited capacity tool magazine. Providing a tool that is needed for a certain processing operation is not in the magazine, a tool switch must occur before the job can be processed, a time/cost consuming operation. To solve this problem, one has to decide three types of decisions, namely, how to select the jobs' sequence (machine loading), which tools to switch before each processing operation (tool loading) and where to locate each tool in the magazine (slot loading). We present an integer programming formulation for the problem and suggest a heuristic procedure to obtain a solution. Our heuristic is partly a generalization of previously suggested approaches to the first two decision types, but it is mainly oriented towards answering the third decision type. The unified problem has not been addressed previously in the literature. We present a numerical study that demonstrates the efficiency of our procedure.     

Capacity allocation problem in flexible manufacturing systems: branch and bound based approaches

This study considers an operation assignment and capacity allocation problem that arises in flexible manufacturing systems. The machines have limited time and tool magazine capacities and the available tools are limited. Our objective is to maximise total weight of assigned operations. We develop a branch and bound algorithm that finds the optimal solutions and a beam search algorithm that finds high quality solutions in polynomial time.     

Optimal tooling policy for a tool switching problem of a flexible machine with automatic tool transporter

This paper addresses a tool switching problem of a flexible machine with the objective of minimizing the frequency of movements of the tool transporter. A flexible machine must process a set of parts with its production sequence already prescribed. It is assumed that the tool magazine cannot hold enough tools for the parts. Thus, tools may have to be switched between two successive parts in the part sequence. Tools that are required but unavailable at the magazine are transferred from the tool crib by an automatic tool transporter with a limited carrying capacity. We suggest an optimal tooling policy utilizing the concept of early insertions of tools and show the effects of early insertions through computational tests on randomly generated test problems.     

Scheduling of the optimal tool replacement times in a flexible manufacturing system

In Flexible Manufacturing Systems (FMSs). a cutting tool is frequently used for different operations and on different part types to minimize tool change-overs and the number of tools required, and to increase part-routing flexibility. In such situations, the tools become shared resources and work in job-dependent, changeable and nonhomogeneous conditions. It is well known that the tool failure rate depends on both age and machining conditions and that tool reliability is a function of the duration, machining conditions, and the sequence of the operations in FMS. The objective of this paper is to obtain a schedule of the optimal preventive replacement times for the cutting tools over a finite time horizon in a flexible manufacturing system. We assume that the tool will be replaced either upon failure during an operation or preventively after the completion of each operation, incurring different replacement costs. A standard stochastic dynamic programming approach is taken to obtain the optimal tool replacement times. The optimal schedule is obtained by minimizing the total expected cost over a finite time horizon for a given sequence of operations. A computational algorithm is developed and a numerical example is given to demonstrate the procedure.     

Biogeography-based optimisation for flexible manufacturing system scheduling problem

Biogeography-based optimisation (BBO) algorithm is a new evolutionary optimisation algorithm based on geographic distribution of biological organisms. With probabilistic operators, this algorithm is able to share more information from good solutions to poor ones. BBO prevents the good solutions to be demolished during the evolution. This feature leads to find the better solutions in a short time rather than other metaheuristics. This paper provides a mathematical model which integrates machine loading, part routing, sequencing and scheduling decision in flexible manufacturing systems (FMS). Moreover, it tackles the scheduling problem when various constraints are imposed on the system. Since this problem is considered to be NP-hard, BBO algorithm is developed to find the optimum /near optimum solution based on various constraints. In the proposed algorithm, different types of mutation operators are employed to enhance the diversity among the population. The proposed BBO has been applied to the instances with different size and degrees of complexity of problem adopted from the FMS literature. The experimental results demonstrate the effectiveness of the proposed algorithm to find optimum /near optimum solutions within reasonable time. Therefore, BBO algorithm can be used as a useful solution for optimisation in various industrial applications within a reasonable computation time.     

Operation allocation and materials-handling system selection in a flexible manufacturing system: A sequential modelling approach

Materials-handling systems are an integrating component of manufacturing operations and as such must be considered within a common framework in manufacturing systems design. This work proposes a first approach to the simultaneous consideration of the operation allocation and the materials-handling system selection problems in a flexible manufacturing system. The objective of the operation allocation model is to select a group of machines where the operations of the part types will be performed and then to assign those operations to the selected machines. The operation allocation model interfaces with the materials-handling system selection model by providing input data in the form of the manufacturing operations to be performed at each machining centre. The selection of the materials-handling system is centred on the matching of the parts visiting a machining centre to perform a manufacturing operation and the abilities of the handling equipment to perform the required materials handling functions of those part types. The objective is to select an optimal group of materials-handling equipment to be assigned to a cell.     

Multi-agent-based approach to solve part selection and task allocation problem in flexible manufacturing systems

Agent technology is currently being considered as an important approach for developing intelligent manufacturing systems. It offers a new way of thinking about many of the classical problems in manufacturing engineering. A multi-agent-based approach for solving the part allocation problems in flexible manufacturing systems (FMS) is presented that can easily cope with the dynamic environment. Four agents were involved in carrying out the tasks of allocating parts on different machines: communicator, machine, part and material handling device (MHD). Upon arrival in the manufacturing facility, the part informs the communicator agent about the task requirements. The communicator agent divides the task into subtasks and sends a call-for-bids message to the machine and MHD agents. Each machine responds in accordance with its process capabilities and buffer limit. This response may be for the whole task or for one or more subtasks and it contains the price and cost details for these subtasks along with the performance index and acceptance ratio of the machine. The final allocation is made based on the objective function that includes processing and transportation costs and time. An algorithm is presented that is used by the communicator agent for allocating parts to different machines. An illustrative example is given to solve the task allocation on five machines, with each machine having different performance index and acceptance ratio.     

The integrated machine allocation and layout problem

Cellular manufacturing has received a considerable amount of attention in the research literature as an approach for improving the performance of manufacturing facilities. However, recent studies have shown that cellular layouts are not always superior to the traditional functional machine layout. We propose a model that does not require the machines to be placed in a functional layout or in a cellular arrangement, but allows the material flow requirements to dictate the machine placement. The model is formulated as an aggregation of the quadratic assignment problem and several network flow problems coupled with linear side constraints. A mixed integer program is presented to find the optimal solution for small problems, and heuristics are developed to solve larger problems. Computational results evaluating the quality of the solution methodologies are also presented.     

Introducing a flexible manufacturing system

Flexible Manufacturing Systems represent a significant investment and their introduction involves a major project for a company. This paper refers to the introduction of FMS in a company. It discusses various management aspects of the project, and its main subject is the simulation modelling of the system. The objectives of the simulation studies are given and the model described. Results are given and commented on, whereby certain capacity limitations were identified. As a result of the studies, weaknesses in the supplier's control software were highlighted and modifications made.     

Loading a flexible manufacturing system

This paper examines the problem of master scheduling for an FMS in Scotland containing six CNC horizontal boring machines. A multiple criteria approach is used to choose the compatible subset of candidate orders for processing by this FMS, subject to resource constraints and potentially conflicting performance objectives. A structured framework for conflict resolution is described and compromise solutions are obtained using standard mathematical programming software.