A method for the concurrent design and analysis of networked manufacturing systems

Multistage manufacturing processes (MMPs) require multiple stations and operations. Traditionally, analysis of MMPs focused on material planning and control strategies. For a given MMP, the effect of the strategy on the volume and rate of production, ability to handle product type variability, and the effects of process variability on production rate, on-process inventory, etc., have been studied individually. Such approaches, while necessary, do not address the combined effects of MMP design choices on the final product quality. In this article, a method based on the compromise decision support problem and stream of variation model is proposed to provide a way to evaluate suitable designs for the implementation of MMPs. Using the dimensional quality of the product as a measure of quality, the proposed method is illustrated using a three-stage MMP in an automobile panel stamping process while considering the conflicting requirements of diagnosability and controllability.     

Influencing factors of synchronization in manufacturing systems

Manufacturing systems exhibit two types of synchronisation phenomena: logistics and physics. Previous research has established synchronisation measures for both types and has shown that they are related to the due date performance. However, there is a lack of knowledge about the factors triggering synchronisation emergence as well as a holistic understanding of synchronisation effects on logistics performance. Thus, this research aims to further explore the relation between synchronisation, its influencing factors and its effect on logistics performance. Based on a profound literature review, we derive first hypotheses on the cause-and-effect-relationships between structural and dynamic properties of a manufacturing system and the emergence of logistics and physics synchronisation as well as logistics performance. By conducting a discrete-event simulation study on diverse manufacturing system types (line, flow shop and job shop production), we are able to test these hypotheses. We conclude that manufacturing network architecture as a structural property as well as processing time variability and system workload as dynamic properties may be exploited for an advanced and synchronisation-oriented manufacturing system design.     

Simulation in the design and operation of manufacturing systems: state of the art and new trends

As the industrial requirements change at a rapid pace due to the drastic evolution of technology, the necessity of quickly investigating potential system alternatives towards a more efficient manufacturing system design arises more intensely than ever. Manufacturing systems simulation has proven to be a powerful tool for designing and evaluating a manufacturing system due to its low cost, quick analysis, low risk and meaningful insight that it may provide, improving thus the understanding of the influence of each component. Simulation comprises an indispensable set of IT tools and methods for the successful implementation of digital manufacturing. It allows experimentation and validation of product, process, and system design and configuration. This paper investigates the major historical milestones in the evolution of manufacturing systems simulation technologies and examines recent industrial and research approaches in key fields of manufacturing. It describes how the urge towards digitalisation of manufacturing in the context of the 4th Industrial revolution has shaped simulation in the design and operation of manufacturing systems and reviews the new approaches that have arisen in the literature. Particular focus is given to technologies in the digitalised factories of the future that are gaining ground in industrial applications simulation, offering multiple advantages.     

Modelling and analysis of energy footprint of manufacturing systems

Increasing the energy efficiency of manufacturing plants will reduce the production costs and environmental impact. In order to analyse and improve the energy efficiency of manufacturing plants, however, we need models to evaluate the energy footprints of the plants. A key challenge of estimating plant-level footprints is that systemic methods of connecting information on the product, machine and plant levels are not available. Thus, we propose methods to parameterise product-level elements and to model machine-level factors based on those elements. From the machine-level models, the proposed approach performs simulation experiments and provides the energy footprints in closed-form equations for the plant level. We also suggest that the resulting model can be combined with probabilistic techniques to benchmark the energy efficiency of plants at the industry level. In a case study, we demonstrate how to apply the proposed methods to estimate the energy footprint of a hypothetical plant. The procedures introduced here enable manufacturers to evaluate the energy consumption of their facilities at early stages of manufacturing, and provide tools to assess the energy efficiency of their plant by comparison with peers.     

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.     

A proposed occupational health and safety risk estimation tool for manufacturing systems

There are numerous hazards to be found in almost any workplace. Annually, millions of workers die, are injured or become ill as a result of these occupational hazards. Industrial machines are often involved in these occupational accidents. Because of the demands of regulatory compliance, and the potentially high cost in terms of human suffering and lost production, businesses should place particular emphasis on safety measures. Risk is defined as a combination of the probability of harm and the severity of its consequences. Generally, risk estimation involves examining the hazards associated with a situation or with the use of a machine. A large number of techniques have been proposed for risk estimation, and recent studies have revealed that some of them have serious flaws. The main objective of this paper is to develop a proposed risk assessment tool based on the findings of an earlier study. Our research results constitute a first step towards the integration of occupational health and safety (OHS) concerns into facility planning models which traditionally do not consider OHS. The proposed risk estimation tool is developed based on the characteristics, strengths and weaknesses of 31 existing risk estimation tools, and is then applied to 20 scenarios representing different hazardous situations. To evaluate the performance of the proposed tool, the results were compared with those of other risk estimation tools and confirmed its proposed ability to estimate risk relative to other risk estimation tools.     

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.     

Extending the information-theoretic measures of the dynamic complexity of manufacturing systems

This paper revisits and extends the structural and dynamic complexity measures of manufacturing systems, which are based on an information-theoretic interpretation of the amount of information that is needed to describe the state of a manufacturing system. In this paper, a generic manufacturing system is modelled as a set of interacting resources and queues. At any moment in time, the combined specific states of the resources and queues define the overall state of the manufacturing system. The main contribution of this paper is a set of dynamic complexity measures that quantify the rate at which information is generated by the facility, and which may be applied with or without reference to the facility's schedule. A worked example demonstrates the step-by-step calculations to obtain values of the complexity measures, and guidance is provided on how to obtain the data needed to carry out the calculations. The links between these complexity measures and the behaviour of a facility are identified and described.     

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.     

Computational modelling of manufacturing choice complexity in a mixed-model assembly line

Manufacturing systems have evolved to adopt a mixed-model assembly line enabling the production of high product variety. Although the mixed-model assembly system with semi-automation (i.e. human involvement) can offer a wide range of advantages, the system becomes very complex as variety increases. Further, while the complexity from different options can worsen the system performance, there is a lack of quantifiable models for manufacturing complexity in the literature. Thus, in this paper, we propose a novel method to quantify manufacturing choice complexity for the effective management of semi-automated systems in a mixed-model assembly line. Based on the concept of information entropy, our model considers both the options mix and the similarities between options. The proposed model, along with an illustrative case study, not only serves as a tool to quantitatively assess the impact of choice complexity on total system performance, but also provides an insight into how complexity can be mitigated without affecting the overall manufacturing throughput.     

Parts-mix analysis in recycling-oriented manufacturing systems for multiple-item production

One solution to environmental problems is to construct a recycling-oriented manufacturing system, in which waste products after consumption are collected, and reusable parts in the collected products are employed to produce new products. A parts-mix in the manufacturing system for multiple-item production is analysed by taking into consideration the merits and demerits of the usage of common parts over multiple products and special parts utilized for individual products. The parts-mix problem is formulated to minimize the life-cycle cost, which consists of production costs and recycling costs. The property of the optimal parts-mix is clarified, and a decision procedure to solve the parts-mix is developed. The procedure decides whether the common parts are effective or not.     

A possibilistic approach for designing hybrid cellular manufacturing systems

In this paper, a hybrid cellular manufacturing (HCM) system is presented in which the main sources of uncertainty, e.g. the demands of parts and unit costs are treated as fuzzy numbers in the form of possibilistic distributions. The basic concept of HCM is that high variation in demand might disturb cell efficiency, so forming cells with only those parts that have stable demand, will profit. Thus, to design stable and robust manufacturing cells, a two-phase method is proposed in which a fuzzy adaptive ranking method is first applied to identify those parts with low and non-repetitive demands (i.e. the special parts) which will then be assigned to a functional cell. Afterwards, an interactive possibilistic programming model is applied to cell formation of remaining regular parts while considering both part sequences and multiple routes. To show the capability and usefulness of the proposed method, an illustrative example is also provided. Finally, concluding remarks are reported.     

Axiomatic design of hybrid manufacturing systems in erratic demand conditions

In order to respond to part demands on time in an erratic demand environment, a complete road map for the design of hybrid cellular manufacturing systems (HMS) is proposed in this study, based on axiomatic design (AD) principles, such that all functional requirements of a complete HMS design are satisfied by the corresponding design parameters. With this methodology, first, a preliminary HMS is formed including exceptional operations. To facilitate one-piece flow within the cells of the HMS, these exceptions are eliminated by the proposed decision rules, where alternative machines are employed (Satoglu et al. 2010). Then, the sufficiency of current resource capacities is verified, using a simulation technique. In other words, stock accumulations are identified and then value stream through the system without any obstacles is ensured. These are achieved by means of procedures for identifying and eliminating the bottleneck resources. The proposed methodology is completed with the HMS layout design. This complete methodology based on AD principles is a unique aspect of this study. The methodology is applied on the data of an automotive supplier, and the results are discussed. Finally, using simulation models, it is shown that applying the proposed model results in a statistically significant improvement in lead time of the current available system.     

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.     

Markovian models for deadlock analysis in automated manufacturing systems

Deadlocks constitute a major issue in the desing and operation of discrete event systems. In automated manufacturing systems, deadlocks assume even greater importance in view of the automated operation. In this paper, we show that Markov chains with absorbing states provide a natural model of manufacturing systems with deadlocks. With illustrative examples, we show that performance indices such as mean time to deadlock and mean number of finished parts before deadlock can be efficiently computed in the modelling framework of Markov chains with absorbing states. We also show that the distribution of time to deadlock can be computed by conducting a transient analysis of the Markov chain model.     

A computational control implementation environment for automated manufacturing systems

This paper presents a computational environment as a tool for supporting the implementation of control coding of an automated manufacturing system. The proposed environment considers a cyclic three-stage control development – modelling, synthesis and implementation – until the real system accomplishes the required specification, resulting in the automated and integrated manufacturing system. The research details the three stages and describes the steps executed for each one. The mathematical formalism used in this work is also presented, as a basis for control implementation. The implementation environment is proposed in order to validate the control structure of this formalism and to allow a progressive integration of control hardware and software. To submit to a test and validate the proposal environment, two experiments are performed, in two different manufacturing systems. Thus, it is demanded that the control system can be reconfigurable in a fast and reliable way.     

Interoperable manufacturing knowledge systems

For many years now, the importance of semantic technologies, that provide a formal, logic-based route to sharing meaning, has been recognised as offering the potential to support interoperability across multiple-related applications and hence, drive manufacturing competitiveness in the digital manufacturing age. However, progress in support of manufacturing enterprise interoperability has tended to be limited to fairly narrow domains of applicability. This paper presents a progression of research and understanding, culminating in the work undertaken in the recent EU FLEXINET project, to develop a comprehensive manufacturing reference ontology that can (a) support the clarification of understanding across domains, (b) support the ability to flexibly share information across interacting software systems and (c) provide the ability to readily configure company knowledge bases to support interoperable manufacturing systems.     

Reliability analysis of a flexible manufacturing cell

In this study, mathematical models are developed to study and compare the operations of a fully reliable and an unreliable flexible manufacturing cell (FMC), each with a flexible machine, a loading/unloading robot, and a pallet handling system. The operation times, loading/unloading times, and material handling times by the pallet are assumed to be random. The operation of the reliable cell is compared to that of an unreliable cell with respect to utilization of the cell components, including the machine, robot, and pallet handling system. The unreliable cell is assumed to operate under random (machine and robot) failures with constant failure rates for the machine and the robot. The pallet handling system is assumed to be completely reliable.     

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.     

Multi-criteria risk analysis to improve safety in manufacturing systems

The drive to lower operating costs and improve manufacturing efficiency has led many manufacturing companies to implement different methodologies in order to identify a suitable risk assessment model. So, the concern for safety in industrial activities, both inside the establishments and in their surroundings, has a crucial role. As a result, many laws, regulations and risk analysis techniques are well adapted to industry needs since they were developed for its purpose. However increasing safety is often difficult, especially when you have already obtained good results, so the aim of our paper is the proposal of a new methodological approach called the safety improve risk assessment (SIRA) by integrating the conventional aspects of the popular failure mode, effects, and criticality analysis (FMECA) procedure with economic considerations in order to take into account the risk and to minimise the total safety costs by defining a specific index called total risk priority number (TRPN) index. The index proposed is based on the improved risk priority number (IRPN) and the analytic network process (ANP), a multi-criteria decision-making technique.