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.     

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.     

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.     

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 reactive GRASP and Path Relinking for balancing reconfigurable transfer lines

A line balancing problem for reconfigurable transfer lines with sequence-dependent setup times and parallel machines was studied. These lines are paced and serial, i.e. a part to be machined passes through a sequence of stations. Stations are composed of CNC (Computer Numerical Control) machines. At least one CNC machine is installed at each station. These CNC machines are mono-spindle head machines, hence setup times between operations have to be taken into account. The origins of setup times are various, for example, the necessity to rotate the part, change and displace the tool, etc. Because of setup times, the station workload depends on the sequence in which the operations are assigned to the station. In addition, accessibility constraints have to be considered. The objective consists of assigning a given set of operations as well as machines to a sequence of workstations in order to minimise the total cost of the line. Keeping in mind the industrial importance of this problem and the lack of available methods in the literature tackling it efficiently, we propose a new heuristic based on GRASP combined with Path Relinking. A MIP approach is used to select the sequences of operations on workstations. Numerical experiments are presented and show that the proposed heuristic can provide good solutions even for large-sized instances while requiring a computational time that is fully compatible with a practical application. An industrial case study is also described.     

A comprehensive approach to operation sequence similarity based part family formation in the reconfigurable manufacturing system

The industrial sector of the twenty-first century faces a highly volatile market in which manufacturing systems must be capable of responding rapidly to the market changes, while fully exploiting resources. The reconfigurable manufacturing system (RMS) is a state of the art technology offering the exact functionality and capacity needed, which is built around a part family. The configuration of an RMS evolves over a period to justify the needs of upcoming part families. The foundation for the success of an RMS, therefore, lies in the recognition of appropriate sets of part families. In the present work the authors have developed a novel operation sequence based BMIM (bypassing moves and idle machines) similarity coefficient using longest common subsequence (LCS) and the minimum number of bypassing moves and the quantity of idle machines. The effectiveness of the developed similarity coefficient has been compared with the existing best similarity/dissimilarity coefficients available in the existing literature. An example set of parts has been classified using the developed similarity coefficient and average linkage hierarchical clustering algorithm. The developed approach can also be used very effectively for part family formation in the cellular manufacturing system.     

Value creation through design for scalability of reconfigurable manufacturing systems

Rapid and cost-effective scalability of the throughput of manufacturing systems is an invaluable feature for the management of manufacturing enterprises. System design for scalability allows the enterprise to build a manufacturing system to supply the current demand, and upgrade its throughput in the future, in a cost-effective manner, to meet possible higher market demand in a timely manner. To possess this capability, the manufacturing system must be designed at the outset for future expansions in its throughput to enable growths in supply exactly when needed by the market. A mathematical method that maximises the system throughput after reconfiguration is proposed, and an industrial case is presented to validate the method. The paper offers a set of principles for system design for scalability to guide designers of modern manufacturing systems.     

Joint optimisation of production rate and preventive maintenance in machining systems

This paper studies an integrated control strategy of production and maintenance for a machining system which produces a single type of product to meet the constant demand. Different from previous research, we assume in this study that during the production, the production rate not only influences the life of cutting tool, but also the reliability of the machine. Both the replacement of cutting tool and the preventive maintenance (PM) of machine are considered in this paper. The machine is preventively maintained at the Nth tool replacement or correctively repaired at the machine failure, whichever occurs first. PM and corrective repair may cause shortage which can be reduced by controlling inventory. There are two decision variables p and N, where p denotes the production rate and N denotes the number of cutting tool replacement before the PM is performed. An integrated model is developed to simultaneously determine the optimal production rate and PM policy that minimise the total expected cost per unit item produced. Finally, an illustrative example and sensitivity analysis are given to demonstrate the proposed model.     

An approach to identify the optimal configurations and reconfiguration processes for design of reconfigurable machine tools

A reconfigurable machine tool (RMT) is a special machine that can deliver different machining functions through reconfiguration processes among its configurations during the machine utilisation stage. In this research, a new approach is developed to identify the optimal configurations and the reconfiguration processes for design of the RMTs. In this work, a generic design AND-OR tree is used to model different design solution candidates, their machine configurations and parameters of these configurations. A specific design solution is created from the generic design AND-OR tree through tree-based search and modelled by different machine configurations. For a reconfiguration process between two machine configurations, a generic process AND-OR graph is used to model reconfiguration operation candidates, sequential constraints among operations and operation parameters. A graph-based search is used to generate all feasible reconfiguration process candidates from the generic process AND-OR graph. The optimal design is identified by multi-level and multi-objective hybrid optimisation. A case study is developed to show how this new approach is used for the optimal design of a RMT.     

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.     

Studying unbalanced workload and buffer allocation of production systems using multi-objective optimisation

Numerous studies have investigated the effects of unbalanced service times and inter-station buffer sizes on the efficiency of discrete part, unpaced production lines. There are two main disadvantages of many of these studies: (1) only some predetermined degree of imbalance and patterns of imbalance have been evaluated against the perfectly balanced configuration, making it hard to form a general conclusion on these factors; (2) only a single objective has been set as the target, which neglects the fact that different patterns of imbalance may outperform with respect to different performance measures. Therefore, the aim of this study is to introduce a new approach to investigate the performance of unpaced production lines by using multiple-objective optimisation. It has been found by equipping multi-objective optimisation with an efficient, equality constraints handling technique, both the optimal pattern and degree of imbalance, as well as the optimal relationship among these factors and the performance measures of a production system can be sought and analysed with some single optimisation runs. The results have illustrated that some very interesting relationships among the key performance measures studied, including system throughput, work-in-process and average buffer level, could only be observed within a truly multi-objective optimisation context. While these results may not be generalised to apply to any production lines, the genericity of the proposed simulation-based approach is believed to be applicable to study any real-world, complex production lines.     

Development of a production cost estimation framework to support product family design

The main task of a product family designer is to decide the right components/design variables to share among products to maintain economies of scale with minimum sacrifice in the performance of each product in the family. The decisions are usually based on several criteria, but production cost is of primary concern. Estimating the production cost of a family of products involves both estimating the production cost of each product in the family and the costs incurred by common and variant components/design variables in the family. To estimate these costs consistently and accurately, we propose a production cost estimation framework to support product family design based on activity-based costing (ABC), which consists of three stages: (1) allocation, (2) estimation, and (3) analysis. In the allocation stage, the production activities and resources needed to produce the entire products in a family are identified and classified with an activity table, a resource table, and a production flow. To help allocate product data for production, a product family structure is represented by a hierarchical classification of products that form the product family. In the estimation stage, production costs are estimated with cost estimation methods selected based on the type of information available. In the analysis stage, components/design variables possible for product family design are investigated with resource sharing methods through activity analysis. As an example, the proposed framework is applied to estimate the production cost of a family of cordless power screwdrivers that share different components within the family.     

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.     

A methodology integrating Petri nets and knowledge-based systems to support process family planning

Planning production processes for product families have been well recognised as an effective means of achieving successful product family development. However, most existing approaches do not lend themselves to planning production processes with focus on the optimality of the cohort of a product family. This paper addresses process family planning for product families. In view of the advantages of Petri nets (PNs) for modelling large systems, the potential of knowledge-based systems (KBSs) for solving complex problems and the analogy in between, we develop a methodology by integrating PNs and KBSs to support process family planning. An integrated product–process family structure, called IP²S, is proposed to organise all data pertaining to a product family and the corresponding process family, thereby anchoring planning to one platform. With the IP²S, a formal PN model of process family planning is further developed by integrating the principles of several well-defined PN extensions. Thus, this paper also contributes to visualising the dynamic behaviours and reasoning behind process family planning. The methodology is applied to process family planning for a truck family. The preliminary results demonstrate the feasibility and potential of using the methodology to support process family planning.     

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.     

A framework for characterising energy consumption of machining manufacturing systems

Energy consumption in machining manufacturing systems is increasingly of interest due to concern for global climate change and manufacturing sustainability. To utilise energy more effectively, it is paramount to understand and characterise the energy consumption of machining manufacturing systems. To this end, a framework to analyse energy consumption characteristics in machining manufacturing systems from a holistic point of view is proposed in this paper. Taking into account the complexity of energy consumption in machining manufacturing systems, energy flow is described in terms of three layers of machining manufacturing systems including machine tool layer, task layer and auxiliary production layer. Furthermore, the energy consumption of machining manufacturing systems is modelled in the spatial and temporal dimensions, respectively, in order to quantitatively characterise the energy flow. The application of the proposed modelling framework is demonstrated by employing a comprehensive analysis of energy consumption for a real-world machining workshop. The characteristics of energy consumption for machine tool layer, task layer and auxiliary production layer are, respectively, obtained using quantitative models in the spatial and temporal dimensions, which provides a valuable insight into energy consumption to support the exploration of energy-saving potentials for the machining manufacturing systems.     

A tool for the conceptual design of production and operations systems

This paper proposes a conceptual design tool, based upon inferential design theory. It has been specifically developed for the design of production and operations systems, but its use can be extended to other engineering areas, such as mechanical and structural systems. Inferential design theory and its foundation in the inferential theory of learning are briefly outlined. Both theories are based on the idea of using specialised knowledge operators in learning and design, termed knowledge transmutations and design knowledge transmutations respectively. The 24 transmutations existing in the two theories are outlined, and a further 12 design-specific transmutations are proposed. These have been developed as a result of our research. A conceptual design process is proposed, in which design knowledge transmutations are used. A software tool for design, CREDO, is also described and an example of its use in the generation of design concepts for an after-sales service facility is presented. The conclusions discuss the initial methodological experience of using CREDO to generate design concepts. They are based on the introductory use of CREDO at Technion in Israel for teaching purposes. Directions for further research are also provided.     

A cost estimation model to support automation decision in assembly systems design

Cost analysis is crucial in the design of assembly systems and the decision on their level of automation (LoA). This paper presents a cost estimation model of assembly system that is used to decide their LoA during the early phase of projects. Based on an extensive literature review, a complete cost model integrating multiple cost drivers is proposed. This model is then exploited to create the objective function of an integer linear programme model utilised to solve the LoA decision problem. The work provides a way to perform cost estimation of assembly systems alternatives and to decide the most appropriate LoA in assembly. The cost estimation model is built with a parametric approach allowing the definition of various optimisation objectives. The proposed integer programme, complement this approach by proposing the suitable constraints set, that describes the LoA decision problem.     

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.