Production control of hybrid manufacturing–remanufacturing systems under demand and return variations

Hybrid manufacturing systems that use both raw materials and returned products as a supply for their production process are considered. Specifically, the system under study contains two machines: one uses raw materials for manufacturing, while another utilises end-of-life products returned from the market for remanufacturing. Machines are failure-prone, demand and return rates fluctuate in time reflecting market behaviour due to economical, seasonal and environmental changes. The system performance is characterised by a long-term discounted cost that integrates several partial costs (those of manufacturing, remanufacturing, disposal, holding costs in serviceable and return inventories). Optimisation of the hybrid system behaviour requires to determine the combined manufacturing, remanufactruring and disposal policy, withstanding machine failures under dynamic market conditions. Optimality conditions in the form of Hamilton–Jacoby–Bellman equations are obtained and a novel numerical approach, based on the estimation of value function timederivative, is proposed in order to deal with demand and return variations. Extensive simulations are performed to address the numerous scenarios corresponding to evolving relationship between manufacturing capacities and varying demand and return levels. Simulation results show that the optimal policies have an important property of anticipating the future changes in the demand and return, and making the timely decisions relevant to these changes.     

Selection of management accounting systems in Just-In-Time and Theory of Constraints-based manufacturing

In today's competitive business environments, a firm's long-term survival rests heavily on its ability to sustain manufacturing superiority over its competitors. To provide the firm with detailed guidelines for sustaining manufacturing superiority, this paper examines the impact of different management accounting systems, manufacturing control systems and time horizon on manufacturing performance in an enterprise resource planning integrated environment. These management accounting systems include traditional costing, activity-based costing and throughput accounting. The manufacturing control systems include Just-In-Time- and Theory of Constraints-based manufacturing. Through a series of simulation experiments, it was found that activity-based costing provided higher short- and long-term profit, better customer service and lower work-in-process inventory than traditional costing and throughput accounting in situations where firms have high overhead costs and relatively low labour and material costs, while carrying ending inventories because of demand uncertainty. Traditional costing also outperformed throughput accounting by exploiting the real-time information sharing capabilities of an enterprise resource planning system. Just-In-Time manufacturing outperformed Theory of Constraints with respect to short- and long-term profitability, customer service, and work-in-process inventory because of differences in buffer inventory policies and sequencing rules. However, time horizon and its interaction with management accounting systems had no impact on the manufacturing performance. In addition, the results suggest that a management accounting system that depicts the manufacturing process tended to provide more accurate product cost information and resulted in a better system performance than the others.     

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.     

RAPID for high-performance computing systems: architecture and performance evaluation

The limited bandwidth and the increase in power dissipation at longer communication distances and higher bit rates will create a major communication bottleneck in high-performance computing systems (HPCS), affecting not only their performance, but also their scalability. As a solution, we propose an optical-interconnect-based architecture for HPCS called reconfigurable all-photonic interconnect for parallel and distributed systems (RAPID) that alleviates the bandwidth density, optimizes power consumption, and enhances scalability. We also present two cost-effective design alternatives of the architecture, a modified version called M-RAPID and an extended version called E-RAPID that minimizes the cost of the interconnect based on the number of transmitters required. We perform a detailed simulation of the proposed RAPID architecture and compare it to several electrical HPCS interconnects. Based on the performance study, RAPID architecture shows 30%-50% increased throughput and 50%-75% reduced network latency as compared to HPCS electrical networks.     

Agent-based distributed scheduling for virtual job shops

Nowadays, market globalisation and stiff world-wide competition require flexible, demand-driven, and reconfigurable production systems that can adapt to the requirements of the increasing reduction in product life cycle and rapid changes in market demand. The advent and development of network technology (especially the Internet) and distributed computing technology make it possible for geographically dispersed manufacturing resources to be integrated and deployed effectively and efficiently. In addition, manufacturing enterprises can expand their throughput within a short time and rapidly reduce the production cycle via transferring certain jobs to other available manufacturing resources in the globalised manufacturing environment, viz., manufacturing enterprises can expand their throughput through the dynamic formation of virtual job shops according to the production requirements. Owing to more open manufacturing environments and rapid changes of market demands, the traditional centralised scheduling approaches are not suitable for this open distributed manufacturing environment. This paper proposes a distributed scheduling approach in which a multi-agent solution towards a ‘task-machine’ assignment is presented. The main points of discussion are the formation of a virtual job shop that is based on market mechanism and the distributed scheduling approach based on negotiation.     

A review of “Advances in Computer-Integrated Manufacturing.” Edited by Peter J. Sacket (JAI Press Ltd., 1990) [pp. 188]. Price £ 48, US $ 81·95.

Global competition and rapidly changing customer requirements are forcing major changes in the production styles and configuration of manufacturing organizations. Traditional centralized manufacturing systems are not able to meet such requirements. This paper proposes an agent-based approach for dynamically creating and managing agent communities in such widely distributed and everchanging manufacturing environments. After reviewing the research literature, an adaptive multi-agent manufacturing system architecture called MetaMorph is presented and its main features are described. Such architecture facilitates multi-agent coordination by minimizing communication and processing overheads. Adaptation is facilitated through organizational structural change and two learning mechanisms: learning from past experiences and learning future agent interactions by simulating future dynamic, emergent behaviours. The MetaMorph architecture also addresses other specific requirements for next generation manufacturing systems, including scalability, reliability, stability, maintainability, flexibility, real-time planning and scheduling, standardized communication, fault tolerance, and security. The proposed architecture is implemented as a multi-agent virtual manufacturing system, in simulation form, which incorporates heterogeneous manufacturing agents within different agent-based shop floors or factories. The experimental results have shown the potential of the agent-based approach for advanced manufacturing systems.     

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.     

Determination of batch size at a bottleneck machine in manufacturing systems

In manufacturing systems, there often exists a bottleneck machine whose capacity is equal to or less than the market demand. Any idle or waste time at the bottleneck machine directly impacts the output of the entire plant because it results in a loss of throughput. In order to maximize the capacity utilization by less setup losses at the bottleneck machine, the parts are often produced in batches. Traditionally, most batch sizing decisions are made based on the economic order quantity model where setup and inventory holding costs are considered. This paper presents an alternative method to determine batch size at a bottleneck machine. We present a new objective function and cost factors for batch sizing and investigate queuing and throughput models. A linear search algorithm is introduced to find the optimal throughput rate and batch size at the same time. Numerical examples are examined to see how the batching algorithm works.     

Rapid one-of-a-kind product development via the Internet: a literature review of the state-of-the-art and a proposed platform

The historical background of Internet-based product design and manufacturing systems for rapid development of one-of-a-kind (OKP) products is systematically reviewed. By reviewing the existing OKP systems and recent approaches of Internet-based design and manufacturing systems, the requirements for the next generation of OKP systems and the current techniques that can be used to implement Internet-based product design and manufacturing systems for the rapid production of OKP products will be discussed. The problems that emerged from recent developments are reviewed and sorted. The future trends of Internet-based collaborative design, decision support, manufacturing support, supply chain management, workflow management, Internet techniques for product design and manufacturing, product modelling, STEP-based data environment, concurrent engineering, etc., will also be discussed. The reviewed state-of-the-art approaches are used directly or indirectly as references for the development of a new generation OKP systems. A reference system structure for building an Internet-based integrated product development system is then proposed to facilitate rapid development of OKP products.     

Blockchain-based ubiquitous manufacturing: a secure and reliable cyber-physical system

With product customisation and emerging business opportunities, small and medium manufacturing enterprises (SMEs) must find ways to collaborate and share competency in a trustable manner to survive a turbulent market. Therefore, service industry turns to the manufacturing industry and SMEs migrate to cloud manufacturing (CM) and ubiquitous manufacturing. However, existing platforms use centralised networking, which suffers from security, scalability and big-data problems. In this paper, we propose a blockchain-based platform as a trustable network to eradicate third-party problems, which can improve the scalability, security and big-data problems for SMEs. Our proposed platform is developed based on a consortium blockchain which provides a peer-to-peer communication network between the end user and the service provider. We improve existing consensus mechanism and communication protocol based on a cyber-physical system (CPS), via an autonomous agent. Firstly, we provide a review of cloud manufacturing, ubiquitous manufacturing and blockchain-based manufacturing approaches by highlighting the main problems. Then, the proposed platform, blockchain ubiquitous manufacturing (BCUM), is explained, based on its architecture, consensus algorithm and CPS, with the help of autonomous agent communication. The proposed platform has been developed for 3D printing companies which are geographically distributed and tested based on network performance and three practical scenarios.     

Production planning system for a combination of make-to-stock and make-to-order products

This paper deals with the problem of designing a production planning system for a combination of make-to-stock (MTS) and make-to-order (MTO) products where the production facility produces both types of products. Important management points in such production systems are to design an efficient production planning system which can shorten the manufacturing time of MTO products as well controlling the unfilled rate of MTS products to the market demand at a low level. A hierarchical production planning model is introduced in order to design the production planning system. The buffer capacity is set as a design variable for determining production capacity at a higher planning level, and the rule for allocating the production capacity to types of products is adopted as a design variable at a lower level. First, we analyse how these two design variables affect the unfilled rate of MTS products and the average manufacturing time of MTO products. Second, we clarify the relationship of the buffer capacity with the manufacturing time of MTO products and with the required buffer inventory level of MTS products which can maintain the unfilled rate of MTS products to the market demand within an acceptable limit. Third, we show an example of the range of design variables which can control the unfilled rate of MTS products and the manufacturing time of MTO products within their acceptable limits, if the individual limits of the performance measure is given to respond to customer orders quickly.     

Optimal reconfiguration policy to react to product changes

The increasing frequency of product and process modifications may significantly undermine the profitability of those production systems that are designed only on the basis of the current product requirements and eventually on the expectations of future variations of the market volumes. Indeed, the product typically evolves during its life cycle, by changing its technological characteristics and therefore its requirements on the production system. As a consequence, the production system may be forced to run in an inefficient and costly manner because it is no longer consistent with the modified product. This paper describes the reconfiguration problem of production systems and proposes the optimal reconfiguration policy to react to product changes, on uniformly distributed market demand and uniformly distributed technological requirements. A numerical case based on a real problem supports the applicability of the proposed reconfiguration policy.     

Dynamic modelling of surge effect and capacity limitation in supply chains

Agile manufacturing has been defined as the capability of reacting to unpredictable market changes in a cost-effective way, simultaneously prospering from the uncertainty. In many industries, vigorously changing markets are demanding more differentiated products in lower volumes and within shorter delivery times. An uncertain environment challenges the response of supply chains. This paper demonstrates, by using a system dynamic simulation, how agility is built into supply chains. Three simulation models are analysed: first, the demand magnification effect in supply chain is studied. Secondly, the analysis is extended to capacity surge effects. Finally, the trade-off between capacity utilization and lead times is discussed. The analysis recommends smaller order sizes, echelon synchronization and capacity analysis as methods of improving the responsiveness of a supply chain. Evidence is provided from simulation runs and established literature. All three models are system dynamics based replications of well-known effects from the research area of production control.     

A framework for strategically-driven evaluation of enterprise information systems

Within an overall framework of manufacturing and supply systems management (MSM), which involves the activities needed to regulate and optimize a system as it progresses through its life cycle, one important element is a system design interface, which associates strategic concerns with system requirements. This paper is concerned with the structure of a MSM reference model aimed at providing a method of system specification, in order to support the system design and operations functions within the complete MSM framework.     

Virtual engineering in design and manufacturing

Manufacturing systems of the future highly demand that the product data are built into the product model,and smooth data transfer to other computer-aided technologies are enabled.Depending on the type of the manufacturing system,it is envisaged that virtual engineering(VE) technologies play a significant role in integrating the computer-based technologies involved in the product's life cycle.Simulations in a virtual world and exchange of real-time product or design data are among the benefits for today's global oriented manufacturing business.To highlight the significance of design as carrier of product data and the key role played by VE technologies to inter-link design,manufacturing and associated components,this paper presents an overview and analysis of the state-of-the-art VE technologies to indicate potential applications and future research directions.     

Robust design and optimization of material handling in an FMS

Although a significant amount of simulation research has been carried out for design and analysis of flexible manufacturing systems (FMS), it does not provide optimal solutions. In this research, we employ two optimum-seeking methods to design and optimize a manufacturing system. The first method is a Taguchi approach, which uses robust design concept to reduce the output variation. The second method is the response surface methodology (RSM), which combines mathematical and statistical techniques to study the geography of the response surface. The results show that throughput of a selected FMS system can be maximized when both methods are employed.     

An integrated chance-constrained stochastic model for efficient and sustainable supplier selection and order allocation

Effective allocation of scarce resources across supply chain environments is an emerging issue, as enterprises face shortfalls in raw materials, human labour, budgetary resources, equipment, energy and capacity. We consider these related objectives in designing efficient and sustainable supply networks using a multi-objective mixed-integer non-linear programming (MINLP) model for efficient and sustainable supplier selection and order allocation with stochastic demand. Our approach considers sustainability dimensions including economic, environmental and social responsibility, but also seeks to design the most efficient supply network given constraints of the supply market. Enterprise efficiency is assessed using a bi-objective data envelopment analysis (DEA) whose inputs include raw materials, current expenses and labour force capacity. The resulting model is non-convex because of the presence of bilinear terms in DEA-related constraints, so we introduce a multi-stage solution procedure that first uses piecewise McCormick envelopes (PCM) to linearise the bilinear terms. Next, we introduce a set of valid inequalities in order to improve solution time of the problem whose dimension significantly increases after being linearised. We then exploit chance constrained programming approaches to deal with stochastic demand. Finally, a single aggregated objective function is derived using a fuzzy multi-objective programming approach. A manufacturing case study demonstrates the validity of the proposed approach, and its effectiveness in designing a supply network that addresses the ‘triple bottom line’ of people, profit and planet that comprises many sustainability initiatives in an efficient manner.     

Lean,agile or leagile? Matching your supply chain to the marketplace

Many enterprises have pursued the lean thinking paradigm to improve the efficiency of their business processes. More recently, the agile manufacturing paradigm has been highlighted as an alternative to, and possibly an improvement on, leanness. In pursuing such arguments in isolation, the power of each paradigm may be lost, which is basically that agile manufacturing is adopted where demand is volatile, and lean manufacturing adopted where there is a stable demand. However, in some situations it is advisable to utilize a different paradigm on either side of the material flow de-coupling point to enable a total supply chain strategy. This approach we have termed the Leagile Paradigm. This paper therefore considers the effect of the marketplace environment on strategy selection to ensure optimal supply chain performance. Real-world case studies in the mechanical precision products, carpet making, and electronic products market sectors demonstrate the new approach to matching supply chain design to the actual needs of the marketplace.     

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.     

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.