Configuration design of scalable reconfigurable manufacturing systems for part family

Intense global competition, dynamic product variations, and rapid technological developments force manufacturing systems to adapt and respond quickly to various changes in the market. Such responsiveness could be achieved through new paradigms such as Reconfigurable manufacturing systems (RMS). In this paper, the problem of configuration design for a scalable reconfigurable RMS that produces different products of a part family is addressed. In order to handle demand fluctuations of products throughout their lifecycles with minimum cost, RMS configurations must change as well. Two different approaches are developed for addressing the system configuration design in different periods. Both approaches make use of modular reconfigurable machine tools (RMTs), and adjust the production capacity of the system, with minimum cost, by adding/removing modules to/from specific RMTs. In the first approach, each production period is designed separately, while in the second approach, future information of products’ demands in all production periods is available in the beginning of system configuration design. Two new mixed integer linear programming (MILP) and integer linear programming (ILP) formulations are presented in the first and the second approaches respectively. The results of these approaches are compared with respect to many different aspects, such as total system design costs, unused capacity, and total number of reconfigurations. Analyses of the results show the superiority of both approaches in terms of exploitation and reconfiguration cost.     

Modelling reconfigurable manufacturing systems with coloured timed Petri nets

Reconfigurable manufacturing systems (RMSs) have been acknowledged as a promising means of providing manufacturing companies with the required production capacities and capabilities. This is accomplished through reconfiguring system elements over time for a diverse set of individualised products often required in small quantities and with short delivery lead times. Recognising the importance of dynamic modelling and visualisation in decision-making support in RMSs and the limitations of current research, we propose in this paper to model RMSs with Petri net (PN) techniques with focus on the process of reconfiguring system elements while considering constraints and system performance. In view of the modelling challenges, including variety handling, production variation accommodation, machine selection, and constraint satisfaction, we develop a new formalism of coloured timed PNs. In conjunction with coloured tokens and timing in coloured and timed PNs, we also define a reconfiguration mechanism to meet modelling challenges. An application case from an electronics company producing mobile phone vibration motors is presented. Also reported are system analysis and application results, which show how the proposed formalism can be used in the reconfiguration decision making process.     

Delayed reconfigurable manufacturing system

Reconfigurable manufacturing systems (RMS) is a new manufacturing paradigm aiming at providing exactly functionality and capacity needed and exactly when needed. Reconfiguration is the main method to achieve this goal. But, the reconfiguration is an interruption to production activities causing production loss and system ramp-up problem and the ‘exact functionality’ may increase the reconfiguration efforts and aggravate the production loss and the ramp-up time. Therefore, a special RMS – delayed reconfigurable manufacturing system (D-RMS) is proposed to promote the practicality of RMS. Starting from the RMS built around part family with the characteristic of delayed differentiation, whose reconfiguration activities mainly occur in the latter stages of manufacturing system and the former stages have the potential to maintain partial production activities to reduce production loss during reconfiguration. Inspired from this, the basic structure of RMS is divided into two subsystems, subsystem 1 is capable of maintain partial production with a certain more functionality than needed, subsystem 2 reconfigure to provide exactly functionality and capacity of a specific part exactly when needed. And then, the benefits of D-RMS are analysed from inventory and ramp-up time aspects. Finally, a case study is presented to show the implementation process of D-RMS and validates the practicability of D-RMS.     

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.     

Configuration design in scalable reconfigurable manufacturing systems (RMS); a case of single-product flow line (SPFL)

The dynamic nature of today’s manufacturing industry, which is caused by the intense global competition and constant technological advancements, requires systems that are highly adaptive and responsive to demand fluctuations. Reconfigurable manufacturing systems (RMS) enable such responsiveness through their main characteristics. This paper addresses the problem of RMS configuration design, where the demand of a single product varies throughout its production life cycle, and the system configuration must change accordingly to satisfy the required demand with minimum cost. A two-phased method is developed to handle the primary system configuration design and the necessary system reconfigurations according to demand rate changes. This method takes advantage of Reconfigurable Machine Tools in RMS. In fact, by adding/removing modules to/from a specific modular reconfigurable machine, its production capability could be increased, with lower cost. A novel mixed integer linear programming formulation is presented in the second phase of the method to optimise the process of selecting the best possible transformation for the existing machine configurations. Two different cases are designed and solved by implementing the established method. The results of these cases in terms of capital cost, capacity expansion cost, unused capacity and number of transformations, are compared with two hypothetical scenarios. Analyses of the obtained results indicate the efficiency of the proposed approach and offer a promising outlook for further research.     

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.     

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.     

Data envelopment analysis with multiple modes of functioning. Application to reconfigurable manufacturing systems

In principle, data envelopment analysis (DEA) does not consider the possibility, which can occur in practice, of a production system being able to operate in different modes of functioning. In this paper, a new DEA modelling approach is proposed in which the different modes of functioning are taken into account and included in the analysis. The observed input consumption and output production in each mode of functioning is used to derive a mode-specific technology. The overall DEA technology aggregates these mode-specific technologies according to their respective time allocations. The proposed model computes a target operating point for each mode of functioning so that the operation of the overall system is efficient. The proposed approach is applied to assess the technical, cost and allocative efficiency of a reconfigurable manufacturing system. The inputs considered are modules/tools usage, labour and energy consumption. The outputs are the number of units produced of each part type. The production possibility set is determined by previous observations of the system functioning, from which the best practices can be identified. Technical, cost and allocative efficiency scores can be computed. The proposed approach not only generates input cost savings but also lead time reductions.     

Variety and volume dynamic management for value creation in changeable manufacturing systems

In today’s uncertain market and continuously evolving technology, managing manufacturing systems are more complex than ever. This paper studies the dynamics of managing variety and volume to enhance value creation in manufacturers implementing system-level advanced and automated manufacturing technology (AAMT). The demand is composed of heterogeneous customers who make purchasing decisions depending on the variety levels and lead times of the firm’s product offerings. The cost structure adopted calculates profit as the difference between customer value creation rate (VCR) and costs associated with the process of creating this value. Reported results contribute to the variety and volume management literature by offering analytical clarity of factors affecting product platforms and capacity scalability management for systems with AAMT. In addition, insightful answers to the trade-offs between profit maximising market coverage and investments, smoothing demand policies and system stability for this type of environment are presented. Furthermore, the value of market information in deciding the industrial technology investment and also the impact of product life cycle on the same investment is captured.     

Energy-oriented bi-objective optimisation for a multi-module reconfigurable manufacturing system

This paper investigates a multi-module reconfigurable manufacturing system for multi-product manufacturing. The system consists of a rotary table and multiple machining modules (turrets and spindles). The production plan of the system is divided into the system design phase and the manufacturing phase, where the installation cost and the energy consumption cost correspond to the two phases, respectively. A mixed-integer programming model for a more general problem is presented. The objectives are to minimise the total cost and minimise the cycle time simultaneously. To solve the optimisation problem, the ε-constraint method is adopted to obtain the Pareto front for small size problems. Since the ε-constraint method is time consuming when problem size increases, we develop a multi-objective simulated annealing algorithm for practical size problems. To demonstrate the efficiency of the proposed algorithm, we compare it with a classic non-dominated sorting genetic algorithm. Experimental results demonstrate the efficiency of the multi-objective simulated annealing algorithm in terms of solution quality and computation time.     

A participatory systems design methodology for changeable manufacturing systems

The ability to adapt to changes in products, processes and technologies is a key competitive factor. Changeable manufacturing paradigms have emerged to address this need, but the industrial implementation remains challenging. In this paper, a participatory design methodology for changeable manufacturing systems is proposed, including requirements specification, selection of appropriate manufacturing paradigm and suitable physical and logical enablers. The methodology supports companies in determining the potential for and mechanisms of transitioning towards changeable manufacturing systems, based on knowledge of products, production, technologies and facilities. The developed methodology is applicable to both new and existing manufacturing systems. It is demonstrated in two industrial cases which highlight its applicability and differences in the appropriate recommended manufacturing systems transition towards changeability as a result of differences in manufacturing characteristics, change requirements and enablers.     

Making IT fit: the design of integrated manufacturing systems

One of the important implications of information technology (IT) is that it has made possible widespread automation in manufacturing industry. However, the bulk of this has involved discrete automation of single plant items or process elements rather than the total production system. Although the capital cost of such total system automation is a significant factor in slowing the rate of change in this direction, there are also a number of problem issues related to the integration of machines, computers and human systems within manufacture and design. Arguably the types of issue involved are not fully understood and in many cases the technological change is demanding totally new approaches and responses to the design of production systems and the traditional manufacture/design connections.The paper explores some of the issues raised in advanced manufacturing systems, drawing on case study research into the adoption of flexible manufacturing systems as an example of computer-integrated manufacture. It comments on the experience of case study firms and presents some comments on the design problems facing those responsible for integrated manufacturing systems.     

Design of delayed reconfigurable manufacturing system based on part family grouping and machine selection

To improve the convertibility of reconfigurable manufacturing system (RMS), the concept of delayed reconfigurable manufacturing system (D-RMS) was proposed. RMS and D-RMS are both constructed around part family. However, D-RMS may suffer from ultra-long system problem with unacceptable idle machines using generic RMS part families. Besides, considering the complex basic system structure of D-RMS, machine selection of D-RMS should be addressed, including dedicated machine, flexible machine, and reconfigurable machine. Therefore, a system design method for D-RMS based on part family grouping and machine selection is proposed. Firstly, a part family grouping method is proposed for D-RMS that groups the parts with more former common operations into the same part family. The concept of longest relative position common operation subsequence (LPCS) is proposed. The similarity coefficient among the parts is calculated based on LPCS. The reciprocal value of the operation position of LPCS is adopted as the characteristic value. The average linkage clustering (ALC) algorithm is used to cluster the parts. Secondly, a machine selection method is proposed to complete the system design of D-RMS, including machine selection rules and the dividing point decision model. Finally, a case study is given to implement and verify the proposed system design method for D-RMS. The results show that the proposed system design method is effective, which can group parts with more former common operations into the same part family and select appropriate machine types.     

Decision support for design of reconfigurable rotary machining systems for family part production

To remain competitive in currently unpredictable markets, the enterprises must adapt their manufacturing systems to frequent market changes and high product variety. Reconfigurable manufacturing systems (RMSs) promise to offer a rapid and cost-effective response to production fluctuations under the condition that their configuration is attentively studied and optimised. This paper presents a decision support tool for designing reconfigurable machining systems to be used for family part production. The objective is to elaborate a cost-effective solution for production of several part families. This design issue is modelled as a combinatorial optimisation problem. An illustrative example and computational experiments are discussed to reveal the application of the proposed methodology. Insight gained would be useful to the decision-makers managing the configuration of manufacturing systems for diversified products.     

Optimisation for multi-part flow-line configuration of reconfigurable manufacturing system using GA

To facilitate the configuration selection of reconfigurable manufacturing systems (RMS) at the beginning of every demand period, it needs to generate K (predefined number) best configurations as candidates. This paper presents a GA-based approach for optimising multi-part flow-line (MPFL) configurations of RMS for a part family. The parameters of the MPFL configuration comprise the number of workstations, the number of paralleling machines and machine type as well as assigned operation setups (OSs) for each workstation. Input requirements include an operation precedence graph for each part, relationships between operations and OSs as well as machine options for each OS. The objective is to minimise the capital cost of MPFL configurations. A 0-1 nonlinear programming model is developed to handle sharing machine utilisation over consecutive OSs for each part which is ignored in the existing approach. Then a novel GA-based approach is proposed to identify K economical solutions within a refined solution space comprising the optimal configurations associated with all feasible OS assignments. A case study shows that the best solution found by GA is better than the optimum obtained by the existing approach. The solution comparisons between the proposed GA and a particle swarm optimisation algorithm further illustrate the effectiveness and efficiency of the proposed GA approach.     

Use of the manufacturing system design decomposition for comparative analysis and effective design of production systems

The focus of this paper is on the use of the Manufacturing System Design Decomposition (MSDD) to make effective cost and production system design decisions. A comparative study is conducted to illustrate how and why the total cost is reduced when the functional requirements defined by the MSDD are achieved. The ultimate goal of this research was to advance manufacturing and production system development to being guided by engineering science and design rather than the common practice of duplicating another person’s or entity’s notion of the best physical implementation.     

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.     

Virtual fusion: a hybrid environment for improved commissioning in manufacturing systems

Efficiency and quality are major factors contributing to profits in manufacturing systems. Production downtime occurs during commissioning of a new system, adoption of new processes, system faults, or (un)planned maintenance; all of which result in reduced production and profit loss. Current techniques for evaluating change to a manufacturing system rely on simulation and modeling to verify processes, but ignore the physical interactions of the work parts on the system. Implementation techniques to evaluate commissioning focus on identifying issues with the cyber interfaces, ignoring the physical interfaces. To validate the cyber and physical interfaces simultaneously, physical work are sent through the system, resulting in significant costs from scrapped work parts and loss of production time. This research proposes a virtual fusion environment where the physical interfaces between a virtual work part and a manufacturing system can be investigated in real-time, on the physical system, without the expenses associated with physical work parts. The virtual environment includes a virtual fusion filter to monitor discrepancies between the physical and virtual systems, and generate a hybrid virtual-physical input signal to the system level controller for virtualisation of a work part onto a physical system. Experimental demonstrations validate the feasibility of the proposed approach.     

Integrated design approach for virtual production line-based reconfigurable manufacturing systems

Reconfigurable manufacturing systems (RMSs) have been recognized as a new manufacturing paradigm. In light of their enhanced flexibility and responsiveness, RMSs are considered to be mostly applicable to the very dynamic and unpredictable marketplaces of the near future. However, systematic approaches to the design and ramp-up of an RMS have not been well addressed. This paper presents a virtual production line-based (VPL) approach to the design and operation of a reconfigurable manufacturing system. Shop floor attributed finite-capacity automaton and VPL attributed finite-capacity automaton are proposed for modelling the control of an RMS, which leads to ease of control software development. Algorithms for balancing VPLs to maximize the productivity of an RMS are discussed. The results of simulation runs of the proposed methodology and algorithms applied to simplified back-end semiconductor manufacturing are provided.     

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.