Cell design and multi-period machine loading in cellular reconfigurable manufacturing systems with alternative routing

This paper deals with the design and loading of Cellular Reconfigurable Manufacturing Systems in the presence of alternative routing and multiple time periods. These systems consist of multiple reconfigurable machining cells, each of which has Reconfigurable Machine Tools and Computer Numerical Control (CNC) machines. Each reconfigurable machine has a library of feasible auxiliary machine modules for achieving particular operational capabilities, while each CNC machine has an automatic tool changer and a tool magazine of a limited capacity. The proposed approach consists of two phases: the machine cell design phase which involves the grouping of machines into machine cells, and the cell loading phase that determines the routing mix and the tool and module allocation. In this paper, the cell design problem is modelled as an Integer Linear Programming formulation, considering the multiple process plans of each part type as if they were separate part types. Once the manufacturing cells are formed, a Mixed Integer Linear Programming model is developed for the cell loading problem, considering multi-period demands for the part types, and minimising transportation and holding costs while keeping the machine and cell utilisations in each period, and the system utilisation across periods, approximately balanced. An illustrative problem and experimental results are presented.     

A conceptual framework for the generation of simulation models from process plans and resource configuration

Although simulation is a popular tool for modelling and analysing modern manufacturing systems, to model shop floor control systems (SFCSs) in simulation requires quite costly efforts, since they are responsible for resolving various decision problems, such as deadlock, part dispatching, and resource conflict. The objective of the paper is to address a conceptual framework necessary to generate a WITNESS simulation model automatically from graph-based process plans and resource configurations. A graph-based process plan is used to capture part operations, their related resource requirements, and their temporal precedence relationships. A WITNESS simulation model is a graphical representation of shop floor resources with the part flow logic embedded within each resource element. To generate a WITNESS model, a process plan is automatically converted into a machine-centred part routeing graph (MCPRG) and then a transport-tending part routeing graph (TTPRG). The MCPRG implies part flows among machines, in which a node represents a machine and an edge represents a part route. The TTPRG implies part flows among machines and material handling devices, in which a node represents either machine or material handler, and an edge represents a part route. From the TTPRG, the part's input and output rules for each resource can be automatically extracted and plugged into the WITNESS model. The approach proposed in the paper enables manufacturers to generate a simulation model rapidly and effectively for performance measurement, such as bottleneck identification, work in progress, throughput times, dynamic resource utilization, and deadlock, of the SFCSs.     

A priority scheduling approach for flexible job shops with multiple process plans

This paper considers the job shop scheduling problem with alternative operations and machines, called the flexible job shop scheduling problem. As an extension of previous studies, operation and routing flexibilities are considered at the same time in the form of multiple process plans, i.e. each job can be processed through alternative operations, each of which can be processed on alternative machines. The main decisions are: (a) selecting operation/machine pair; and (b) sequencing the jobs assigned to each machine. Since the problem is highly complicated, we suggest a practical priority scheduling approach in which the two decisions are done at the same time using a combination of operation/machine selection and job sequencing rules. The performance measures used are minimising makespan, total flow time, mean tardiness, the number of tardy jobs, and the maximum tardiness. To compare the performances of various rule combinations, simulation experiments were done on the data for hybrid systems with an advanced reconfigurable manufacturing system and a conventional legacy system, and the results are reported.     

Batch versus cyclic scheduling of flexible flow shops by mixed-integer programming

New mixed-integer programming models are proposed for deterministic batch or cyclic scheduling in flow shops with parallel machines and finite in-process buffers. Models for scheduling with all machines continuously available for processing throughout the entire scheduling horizon as well as for scheduling with an arbitrary pattern of machine availability due to pre-scheduled downtime events are provided. Numerical examples modelled after real-world flexible flow shop scheduling in electronics manufacturing are presented, and to compare the batch and cyclic schedules with continuous or with limited machine availability, results of computational experiments are reported.     

Scalable reconfigurable equipment design principles

Scalability is one of six key characteristics found in reconfigurable manufacturing systems. Scalable systems satisfy changing capacity requirements efficiently through system reconfiguration, and in the flexible manufacturing literature this capability is called expansion flexibility. The development of modular scalable machine tools is a necessary precursor to achieving scalable systems. Unfortunately, there is little work describing the design of scalable machines. This paper establishes the need for scalable machines and a basis for evaluating and describing them. Applicable metrics are defined, and an architecture for scalable machines is presented. Two examples illustrate the scalable architecture. Finally, a design parameter based on a mathematical approach is presented to determine the optimal number of modules to be included on a modular scalable machine. This as a design parameter is important because it limits machine size and the number of module interfaces included in the base machine structure.     

Recent advances in research on reconfigurable machine tools: a literature review

A recent trend in research on reconfigurable manufacturing systems is the development of reconfigurable machine tools (RMTs). A RMT can be used as a group of machines through change of its configuration to satisfy different manufacturing requirements. A literature review is provided in this paper to demonstrate the state-of-the-art advances and challenges on research and development of RMTs from the perspectives of architecture design, configuration design and optimisation, and system integration and control. In architecture design, semi-open and open architectures based on modular design approach are often selected to allow different modules of the machine to be added and removed. In configuration design and optimisation, operations of reconfiguration processes are analysed and optimised to achieve variety of configurations with the minimum reconfiguration effort. In system integration and control, transfers of motion, energy and data among different modules of the RMT are carried out. The challenges in research on RMTs are also discussed.     

A morphology proposal in commercial-off-the-shelf reconfigurable machine tools

Global manufacturing is continuously facing changing demands, the unpredictable part family supply that a machine tool user has to deal with needs varying machine morphologies. The reconfigurable manufacturing system paradigm proposes the need for the right capacity, for the right demand with an economical ramp-up period. The machinist needs to have a systematic manner of configuring the machines, given a set of modules that will be configured and reconfigured for the various demands in the lifespan of a manufacturing system. In this article, the author proposes how the machinist can go about identifying the different morphologies in advance. The method is simple and user-friendly in consideration of the main users who may have basic skills being deficient in sophistication and complexity; it further assists in the determination of the capability the manufacturer has with the available modules.     

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.     

Manufacturing system development framework using a data models driven approach

We report on a data models driven approach for the development of a manufacturing system framework. Relational data schemes are used for the creation of data models. A modular approach is adopted for the creation of complex manufacturing system configurations. Each module is created by selecting the appropriate resources from the data models and is represented as a standard module template in the module library for future use. Several modules can be integrated together through an automated guided vehicles system to model a complex manufacturing system. Each module is autonomous in creating and executing its plans, but cooperative with other modules to realize the system's overall goals. For effective control of parts in the system, an event-based simulation strategy is implemented. The developed algorithm can resolve the situations arising due to any deadlock or conflict during a simulation run. System data tables are regularly updated as and when an event occurs in the system. The updated information includes machine status, part location and status, and capacity status, etc. of all parts and resources. A case study comprising eight part types with five different flow patterns in a three-module system is taken to show the effectiveness of the proposed approach.     

An immune algorithm for scheduling a hybrid flow shop with sequence-dependent setup times and machines with random breakdowns

Much of the research on operations scheduling problems has either ignored setup times or assumed that setup times on each machine are independent of the job sequence. Furthermore, most scheduling problems that have been discussed in the literature are under the assumption that machines are continuously available. Nevertheless, in most real-life industries a machine can be unavailable for many reasons, such as unanticipated breakdowns (stochastic unavailability), or due to scheduled preventive maintenance where the periods of unavailability are known in advance (deterministic unavailability). This paper deals with hybrid flow shop scheduling problems in which there are sequence-dependent setup times (SDSTs), and machines suffer stochastic breakdowns, to optimise objectives based on the expected makespan. With the increase in manufacturing complexity, conventional scheduling techniques for generating a reasonable manufacturing schedule have become ineffective. An immune algorithm (IA) can be used to tackle complex problems and produce a reasonable manufacturing schedule within an acceptable time. In this research, a computational method based on a clonal selection principle and an affinity maturation mechanism of the immune response is used. This paper describes how we can incorporate simulation into an immune algorithm for the scheduling of a SDST hybrid flow shop with machines that suffer stochastic breakdowns. The results obtained are analysed using a Taguchi experimental design.     

Models for Understanding Flexible Manufacturing Systems

The basic features of flexible manufacturing systems are reviewed and models for determining the production capacity of such systems are developed. These models show the desirability of a balanced work load, the benefit of diversity in job routing if there is adequate control of the release of jobs (a job shop can be better than a flow shop), and the superiority of common storage for the system over local storage at machines. The models are extended to allow for material handling delays between machines and for unreliable machines. It is also shown that production capacity models can be used to develop good approximations to the mean number of jobs in the system for given job arrival rates and machine utilizations.     

Sequencing of robot activities and parts in two-machine robotic cells

This paper deals with the development of analytical methods for determining an optimal sequence of parts and robot activities to minimize cycle time in robotic cells with two machines. A robot is used to feed parts to the two machines or in the absence of machines two robots perform processing operations on parts. Three different types of robotic cellular layouts, namely the robot-centered cell, the mobile robot cell, and the in-line robot cell have been considered in an automated flow line manufacturing system with no storage buffers. Optimal sequences have been established for both single and multiple part types when part production is performed in a repetitive fashion. In order to keep abreast with the current trend toward just-in-time manufacturing, production of a quantity known as the minimum part set (MPS) is considered for multiple part types. The analysis for a single MPS has further been extended to include the cyclic production of multiple MPSs. The problem of determining the optimal sequence of multiple part types has been shown equivalent to a two machines no-wait flow shop problem, and has been solved by Gilmore and Gomory's (1964) algorithm.     

A simple metaheuristic approach to the simultaneous scheduling of machines and automated guided vehicles

In this paper we address the problem of simultaneous scheduling of machines and vehicles in flexible manufacturing systems. The studied problem is a job shop where the jobs have to be transported between the machines by automatic guided vehicles. In addition to the processing of jobs, we consider the transportation aspect as an integral part of the optimization process. To deal with this problem, we propose a new solution representation based on vehicles rather than machines. Each solution can thus be evaluated using a discrete event approach. An efficient neighbouring system is then described and implemented into three different metaheuristics: iterated local search, simulated annealing and their hybridisation. Computational results are presented for a benchmark of 40 literature instances. New upper bounds are found for 11 of them, showing the effectiveness of the presented approach.     

Optimal cost design of flow lines with reconfigurable machines for batch production

Modular reconfigurable machines offer the possibility to efficiently produce a family of different parts. This paper formalises a cost optimisation problem for flow lines equipped with reconfigurable machines which carry turrets, machining modules and single spindles. The proposed models take into account constraints related to: (i) design of machining modules, turrets, and machines, (ii) part locations, and (iii) precedence relations among operations. The goal is to minimise equipment cost while reaching a given output and satisfying all the constraints. A mixed integer programming model is developed for the considered optimisation problem. The approach is validated through an industrial case study and extensive numerical experiments.     

A methodology for design and reconfiguration of reconfigurable bending press machines (RBPMs)

Customer requirements have become very dynamic and unprecedented. A manufacturing paradigm called reconfigurable manufacturing system was initiated to adjust the physical machine entities. The main enabler of a machine structure’s reconfigurability is a modular design approach. The paper explains a function-driven object-oriented methodology for the design and reconfiguration of RBPMs. The complete method aims to optimise initial design of RBPMs, followed by subsequent design of RPBM modules which are stored in a module library so as to enable full-automatic reconfiguration of the RBPMs. The methodology is implemented on a pilot project to design a 145 ton bending capacity RBPM, with a maximum reconfigured length of 5?m and total height of 3?m. In order to deduce the design for the reconfigurable bending press machine, the reconfigurability needs were identified first, followed by the construction of a function tree for the machine. The function tree identifies the primary function for the RBPM, which is to bend sheet metal. The primary function is further decomposed to lower level functions until terminal functions are arrived at. The terminal functions are then used to identify the modules for the machine. The modules implement specific brunches of the machine functions.     

An agent-based negotiation approach to integrate process planning and scheduling

This paper presents the development of an agent-based negotiation approach to integrate process planning and scheduling (IPPS) in a job shop kind of flexible manufacturing environment. The agent-based system comprises two types of agents, part agents and machine agents, to represent parts and machines respectively. For each part, all feasible manufacturing processes and routings are recorded as alternative process plans. Similarly, alternative machines for an operation are also considered. With regard to the scheduling requirements and the alternative process plans of a part, the proposed agent-based IPPS system aims to specify the process routing and to assign the manufacturing resources effectively. To establish task allocations, the part and machine agents have to engage in bidding. Bids are evaluated in accordance with a currency function which considers an agent's multi-objectives and IPPS parameters. A negotiation protocol is developed for negotiations between the part agents and the machine agents. The protocol is modified from the contract net protocol to cater for the multiple-task and many-to-many negotiations in this paper. An agent-based framework is established to simulate the proposed IPPS approach. Experiments are conducted to evaluate the performance of the proposed system. The performance measures, including makespan and flowtime, are compared with those of a search technique based on a co-evolutionary algorithm.     

Adaptive scheduling of batch servers in flow shops

Batch servicing is a common way of benefiting from economies of scale in manufacturing operations. Good examples of production systems that allow for batch processing are ovens found in the aircraft industry and in semiconductor manufacturing. In this paper we study the issue of dynamic scheduling of such systems within the context of multi-stage flow shops. So far, a great deal of research has concentrated on the development of control strategies, which only address the batch stage. This paper proposes an integral scheduling approach that also includes succeeding stages. In this way, we aim for shop optimization, instead of optimizing performance for a single stage. Our so-called look-ahead strategy adapts its scheduling decision to shop status, which includes information on a limited number of near-future arrivals. In particular, we study a two-stage flow shop, in which the batch stage is succeeded by a serial stage. The serial stage may be realized by a single machine or by parallel machines. Through an extensive simulation study it is demonstrated how shop performance can be improved by the proposed strategy relative to existing strategies.     

A new heuristic for integrated process planning and scheduling in reconfigurable manufacturing systems

Integrated process planning and scheduling (IPPS) is a manufacturing strategy that considers process planning and scheduling as an integrated function rather than two separated functions performed sequentially. In this paper, we propose a new heuristic to IPPS problem for reconfigurable manufacturing systems (RMS). An RMS consists mainly of reconfigurable machine tools (RMTs), each with multiple configurations, and can perform different operations with different capacities. The proposed heuristic takes into account the multi-configuration nature of machines to integrate both process planning and scheduling. To illustrate the applicability and the efficiency of the proposed heuristic, a numerical example is presented where the heuristic is compared to a classical sequential process planning and scheduling strategy using a discrete-event simulation framework. The results show an advantage of the proposed heuristic over the sequential process planning and scheduling strategy.     

Evaluation of the logistic model of the reconfigurable manufacturing system based on generalised stochastic Petri nets

To reveal the influence on system performance by the logistic model of reconfigurable manufacturing system (RMS), the generalised stochastic Petri nets (GSPN) modular modelling approach is presented in this paper. It is based upon the characteristics of a bottleneck service. According to this approach, the bottleneck service in the production process is found first. By corresponding different resources in the service to different modules of the GSPN, the module is reconfigured. The analysis of the model using the Markov chain is hereby presented, as is the average utilisation factor of RMS. Following this, the production capacity of different products and the average productivity of reconfigurable manufacturing cells (RMCs) are discussed.     

Production sequencing problem with re-entrant work flows and sequence dependent setup times

This paper addresses a shop scheduling problem where a set of n jobs needs to be scheduled on two machines for the side frame press shop in a truck manufacturing company. A most unusual aspect of the problem is that the setup times required for a job in the first machine depend not on the immediately preceding job but on the job which is two steps prior to it. Redefining the job elements, the problem is formulated into a general two machine flow shop problem which can be solved by dynamic programming with the objective of the minimum makespan. An optimal schedule is found utilizing the sequence dominance conditions and the decisiondelay scheme. Since the computational requirements of dynamic programming are impracticably demanding for large-sized problems, a genetic algorithm is developed and its performance is examined through a comparative study.