Synchronization in manufacturing systems: quantification and relation to logistics performance

The term ‘synchronization’ in manufacturing refers to the provision of the right components to the subsequent production steps at the right moment in time. It is widely assumed that synchronization is beneficial to the logistics performance of manufacturing systems. However, it has been shown that synchronization phenomena can be detrimental to systems in which they emerge. To study if synchronization phenomena also occur in and affect manufacturing systems’ performance, a formal quantification and holistic understanding of the types of synchronization phenomena emerging in manufacturing are needed. This article aims to fill this research gap by developing synchronization measures for manufacturing systems, applying these measures to real-world production feedback data and utilising them to test the assumption about synchronization’s beneficial effect on logistics performance. We identify two distinct synchronization types occurring in manufacturing systems, logistics and physics synchronization, and show that they are negatively correlated. Further, we show that logistics synchronization and due date performance exhibit anti-correlation and thus question the assumption that synchronization leads to higher efficiency in manufacturing systems. This article aids production managers in designing and optimising production systems, and supports further empirical research in production planning and control and production system design.     

Optimal concurrent product design and process planning based on the requirements of individual customers in one-of-a-kind production

One-of-a-kind production is a new manufacturing paradigm for producing customised products based on the requirements of individual customers while maintaining the quality and efficiency of mass production. This research addresses the issues in optimal concurrent product design and process planning based on the requirements of individual customers. In this work, a hybrid AND-OR graph is developed to model the variations of design configurations/parameters and manufacturing processes/parameters in a generic product family. Since different design configurations and parameters can be created from the same customer requirements, and each design can be further achieved through alternative manufacturing processes and parameters, co-evolutionary genetic programming and numerical optimisation are employed to identify the optimal product design configuration/parameters and manufacturing process/parameters. A case study is introduced to identify the optimal design configuration/parameters and manufacturing process/parameters of custom window products of an industrial company to demonstrate the effectiveness of the developed method.     

Performance analysis for serial production lines with Bernoulli Machines and Real-time WIP-based Machine switch-on/off control

In recent years, achieving high energy efficiency has become one of the primary goals in manufacturing, along with maintaining high productivity and quality. In many manufacturing systems, it is sometimes possible to temporarily switch off a machine to reserve energy, and switch it back on when a certain condition is met. Indeed, production control-based shop floor continuous improvement is recognised as one of the most cost-effective ways to achieve energy-efficient production. In this paper, we study serial production lines with Bernoulli machines and finite capacity buffers and assume that some of the machines in the line can be switched on and off during the production process according to a state-based feedback control policy. Mathematical models for the system under consideration are derived and analytical methods are developed for calculating the system performance measures during transients. Specifically, exact Markovian analysis is used for two- and three-machine lines in which the switch-on/off operations of only one machine is considered. For longer lines, the switch-on/off operations of multiple machines are considered and an aggregation-based approximation approach is applied to evaluate the system performance measures. Numerical experiments show that the method developed can be used to efficiently calculate the system’s performance with high accuracy.     

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.     

Optimisation of the transmission of disruptions in assembly systems

The dynamic analysis of disruption transmission in networks of closed loops formed by machines and intermediate buffers is of vital importance in most production systems. Nevertheless, little research has been done on optimisation in this field. This study analyses the disruption time transmission in a generic assembly system, which has been modelled as a network of closed loops of machines and intermediate buffers. In addition, this modelling has been used to analyse a real automobile assembly line, taking into account variables that have not previously been considered in the literature, such as working regimes of machines, their cycle times, capacities of the intermediate buffers and their minimum contents. The optimal configuration of the intermediate buffers is analysed. Dynamic outlines of these kinds of assembly systems are proposed in order to maximise the transmission of disruption times and, hence, their availability. For this purpose, an algorithm for analysing and optimising availability in this kind of manufacturing system has also been developed.     

Nested coloured timed Petri nets for production configuration of product families

Production configuration is as an effective technique to deal with product variety while maintaining production stability and efficiency. It involves a diverse set of process elements (e.g., machines, operations), a high variety of component parts and assemblies and many constraints arising from product and process variety. Production configuration entails the selection and subsequent arrangement of process elements into complete production processes and the final evaluation of configured multiple alternatives. To better understand production configuration and its implementation, we study the underlying logic for configuring production processes using a dynamic modelling and visualisation approach. This is accomplished by developing a new formalism of nested coloured timed Petri nets (PNs). In view of the inherent modelling difficulties, in the formalism three types of nets–process nets, assembly nets and manufacturing nets–together with a nested net system are defined. Using an industrial example of vibration motors, we show how the proposed formalism can be applied to specify production processes at different levels of abstraction to achieve production configuration.     

Axiomatic modelling of agile production system design

The manufacturing organisations are witnessing a transformation in the manufacturing paradigm due to increasing competition. Agile manufacturing (AM) is a contemporary manufacturing paradigm which enables the organisations to survive in this competitive scenario. Design engineering is a vital technological enabler of AM. The research on axiomatic design in the field of AM is found to be feeble. In this context, this paper reports an axiomatic model of agile production system design using process variables. A hierarchical structure has been developed to model the design process of an agile production system composed of functional requirements, design parameters and process variables. In the theory of axiomatic design, process variables are created by mapping the design parameters in the process domain. This article serves as an efficient guideline for the design process to clarify the tools, methods and resources of designing agile production system of Indian electronic switches manufacturing organisation.     

Production and subcontracting control for an unreliable manufacturing system with setups

This paper deals with the problem of joint production, setup and subcontracting control of unreliable manufacturing systems producing two product types. The production requires setups each time it switches from one product type to another. Subcontracting is an integral part of the decision-making process due to limited production capacity in existing facility. The objective is to propose an effective control policy for the considered system which simultaneously manages production, setup and subcontracting activities. The complexity of the problem lies in the interaction between internal manufacturing decisions and subcontracting that outsource a part of the production, in a dynamic and stochastic environment. An experimental optimisation approach is adopted to determine the optimal control parameters which minimise the average total cost. Extensive sensitivity analyses are performed to illustrate the robustness and the usefulness of the adopted approach. An in-depth study comparing five control policies across a wide range of system parameters is also conducted. Extended cases closer to reality are also investigated considering elements such as the preventive maintenance and the production of non-conforming products. The best control policy in terms of economic performance is then obtained. Valuable insights providing a better understanding of interactions involving production, setup, and subcontracting are discussed.     

Design for manufacturing and assembly/disassembly: joint design of products and production systems

Design for Manufacturing, Assembly, and Disassembly is important in today’s production systems because if this aspect is not considered, it could lead to inefficient operations and excessive material usage, both of which have a significant impact on manufacturing cost and time. Attention to this topic is important in achieving the target standards of Industry 4.0 which is inclusive of material utilisation, manufacturing operations, machine utilisation, features selection of the products, and development of suitable interfaces with information communication technologies (ICT) and other evolving technologies. Design for manufacturing (DFM) and Design for Assembly (DFA) have been around since the 1980’s for rectifying and overcoming the difficulties and waste related to the manufacturing as well as assembly at the design stage. Furthermore, this domain includes a decision support system and knowledge base with manufacturing and design guidelines following the adoption of ICT. With this in mind, ‘Design for manufacturing and assembly/disassembly: Joint design of products and production systems’, a special issue has been conceived and its contents are elaborated in detail. In this paper, a background of the topics pertaining to DFM, DFA and related topics seen in today’s manufacturing systems are discussed. The accepted papers of this issue are categorised in multiple sections and their significant features are outlined.     

Layout design in fractal organizations

Today's complex, unpredictable and unstable marketplace requires flexible manufacturing systems capable of cost-effective high variety–low volume production in frequently changing product demand and mix. In fractal organizations, system flexibility and responsiveness are achieved by allocating all manufacturing resources into multifunctional cells that are capable of processing a wide variety of products. In this paper, various fractal cell configuration methods for different system design objectives and constraints are proposed. These parameters determine the level of interaction between the cells, the distribution of different product types among the cells and the similarity of cell capabilities. A tabu-search-based method is proposed to optimize the product distribution to the cells and the arrangement of machines and cells on the shop floor. This optimization is performed for different fractal cell configuration methods and cell quantities. The quality of the resulting shop floor layouts is measured in terms of resource requirements and material movements. The results indicate that in fractal layouts, a trade-off is required between machine quantities and material travelling distance. It was generally possible to reduce travelling distances by increasing the degree of optimization on machine layout and product distribution for a specific product demand and mix.     

RFID-enabled product-service system for automotive part and accessory manufacturing alliances

Automotive part and accessory manufacturers (APAMs) at the lower tiers of automotive vertical supply chains have been responding to major initiatives taken by leading vehicle assemblers in adopting RFID (radio frequency identification) and ubiquitous computing technologies to alleviate their manufacturing systems. RFID-enabled real-time traceability and visibility facilitate and enhance the implementation of advanced strategies such as just-in-time (JIT) lean/responsive manufacturing and mass customisation (MC). This paper reports on findings gained from a series of industrial field and pilot studies conducted within collaborating companies. Being typically small and medium sized, APAMs are faced with business and technical challenges that are summarised by the so-called ‘three high problems’, namely high cost, high risk and high level of technical skills. This research takes a more cost-effective pragmatic approach to overcome the ‘three high problems’ by sharing out the problems among APAMs while taking a longer-term, expensive and lengthy, approach to absolutely reduce the problems. The sharing approach requires the establishment of an innovative service-oriented framework, abbreviated AUTOPS, based on the Product Service Systems (PSS) business model. RFID hardware devices are innovated into gateways as hardcore products to formulate a PSS. RFID-enabled real-time services are deployed at a common platform across members of an APAMs alliance. AUTOPS facilities are shared by APAM alliance members to reduce the start-up investment costs, reduce the level of required specialist skills, speed up installation processes and streamline maintenance services, and improve the reliability of the RFID gateway services.     

A stochastic dynamic programming based model for uncertain production planning of re-manufacturing system

Re-manufacturing is recycling by manufacturing as-good-as-new products from used products, often involving disassembly, cleaning, testing, part replacement/repair, and re-assembly operations. Production planning and inventory control is one of the most important research issues for re-manufacturing system, which are faced with a greater degree of uncertainty and complexity. This leads to a critical need for planning and control systems designed to deal with the added uncertainty and complexity. We formulate a stochastic dynamic programming based model to study the production planning, i.e. dynamic lot sizing problem, of re-manufacturing systems. In the model the demand and return amounts are stochastic over the finite planning horizon. The objective is to determine the quantities that have to be re-manufactured at each period in order to minimise the total cost, including re-manufacturing cost, holding cost for returns and re-manufactured products and backlog cost. The optimal production plan of the re-manufacturing system over a finite planning horizon can be obtained with the policy iteration method. In the end, a numerical example is performed to illustrate how the model is applied and to prove its feasibility.     

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.     

Cost and quality of service analysis of production systems based on the cumulative downtime

The paper presents a method for the analysis and design of industrial production systems based on a joint assessment of the cost and the quality of service. The operation of a production system is seen as the accomplishment of a sequence of missions, each one corresponding to the cost-effective production and delivery of a specified quantity of products within a specified time frame. The paper shows that the probability of successfully accomplishing a mission is a non-linear function of the cumulative production downtime and that this time cannot be obtained using conventional Markov based techniques. The paper also introduces an analytical model and a procedure that allows the density function of the downtime to be obtained and shows how, using these tools, the production costs and the quality of service may be assessed and related to the internal design of the shop floor. The method seems to be particularly valuable in the analysis of production systems integrated in just-in-time supply chains, in which the reliability of the deliveries is an outstanding requirement.     

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.     

Development of a hybrid negotiation scheme for multi-agent manufacturing systems

A hybrid inter-agent negotiation mechanism based on currency and a pre-emption control scheme is proposed to improve the performance of multi-agent manufacturing systems. The multi-agent system considered consists mainly of four types of agents: machine, clone, part and mediator. The machine agent controls the scheduling and the execution of a task. The clone agent aims to maximize the utilization rate by attracting relevant work to the machine. The part agent communicates with the machine agent or clone agent to acquire necessary production resources in order to get the required processing done, and the mediator agent contains the status of the part that will be processed by the subcontracting machine agent. The primary objective is to design decentralized control protocols for discrete part manufacturing systems to enhance the efficiency of the system and to allocate dynamically the resources to critical jobs based on the dynamic search tree. This research incorporates both the currency and the pre-emption schemes within a common framework. Currency functions are used to help the agents meet their individual objectives, whereas the pre-emption scheme is used to expedite the processing of parts based on their due dates. A dynamic search algorithm for the best route selection of different operations based on the job completion time is also proposed and it is implemented on a small manufacturing unit.     

Methods and tools for decision making in engineering design

This paper describes the background to the setting up of the Cambridge Engineering Design Centre. An overview of the design research and applications programme of the Cambridge EDC is given. Four research themes are identified: functional modelling, configuration and manufacturing optimization, materials and process selection, and process interpretation and management. Application areas include aerospace systems, heavy duty vehicles and medical equipment.     

Integrated configurable equipment selection and line balancing for mass production with serial–parallel machining systems

Solving equipment selection and line balancing problems together allows better line configurations to be reached and avoids local optimal solutions. This article considers jointly these two decision problems for mass production lines with serial–parallel workplaces. This study was motivated by the design of production lines based on machines with rotary or mobile tables. Nevertheless, the results are more general and can be applied to assembly and production lines with similar structures. The designers’ objectives and the constraints are studied in order to suggest a relevant mathematical model and an efficient optimization approach to solve it. A real case study is used to validate the model and the developed approach.     

The elementary flux modes of a manufacturing system: a novel approach to explore the relationship of network structure and function

Elementary flux modes (EFMs) are a concept from Systems Biology, where they serve as an indicator of component relevance in metabolic networks. An elementary flux mode is a functionally relevant, non-decomposable path through a given network. In this paper, we apply elementary flux mode analysis to manufacturing systems, with the aim of using the number of EFMs as a predictor for resource significance in the manufacturing system. For this, we formulate a network representation of a manufacturing process, which allows us to define the manufacturing equivalent of a stoichiometric matrix to draw an analogy between metabolic and manufacturing systems. This, in turn, allows the computation of EFMs, which we conduct in a case-study for a real manufacturing system. We further show that the change of EFMs under resource breakdown is a good indicator of the average order lateness in the manufacturing system. In this way, EFMs provide insight into the relationship of network structure and function in manufacturing.