Effects of information transparency and cooperation on supply chain performance: a simulation study

This research explores the effect of information transparency and cooperation among the front nodes of supply chains. Although published works in the supply chain (SC) domain underline the need for information transparency and cooperation for competitiveness of firms, the majority among these are conceptual or empirical. As such, the domain requires fresh effort towards analytical and simulation based research for validation. In the present work, simulation is used as the research methodology. The simulation platform is developed in ARENA®, which is based on simulation language SIMAN. It has the capability to model multi-product, multi-echelon supply chains. Cooperation is depicted in the form of demand pooling and accelerated delivery of consignments from cooperating SC nodes, when stock-out contingency occurs at a particular node. The modelling also explores the effects of full, partial and zero level of information transparency on the SC performance. The simulation results suggest that these initiatives improve SC service time performance. It is also observed that more advantages from cooperation and information transparency are obtainable when the SC is leaner. The studies also highlight that such SC initiative that motivates local optimisation at the nodes is counter-productive to SC wide performance.     

A multi-agent virtual enterprise model and its simulation with Swarm

Virtual enterprise (VE) is a considerably complex organization in the world. More efforts have been made to establish such organization, among which multi-agent modelling and simulation are regarded as a promising approach. In this paper, MAS theory and technology are briefly reviewed. A novel multi-agent VE model is provided with a comparison with related work. Swarm as an outstanding multi-agent simulation programming tool is introduced. A modelling and simulation platform is developed with Swarm. The framework and main components of the platform are illustrated. The procedure of modelling VE on this platform is proposed. A case study using the platform on VE establishment in manufacturing domain is presented, and several common formulae to measure the performance of manufactures are developed in this case study.     

Robot selection using a fuzzy regression-based decision-making approach

Industrial robots, which enable manufacturing firms to produce high-quality products in a cost-effective manner, are important components of advanced manufacturing technologies. The performance of industrial robots is determined by multiple and conflicting criteria that have to be simultaneously considered in a robust selection study. In this study, a decision model based on fuzzy linear regression is presented for industrial robot selection. Fuzzy linear regression provides an alternative approach to statistical regression for modelling situations where the relationships are vague or the data set cannot satisfy the assumptions of statistical regression. The results obtained by employing fuzzy linear regression are compared with those of earlier studies applying different analytical methods to a previously reported robot selection problem.     

智能家居综合实验平台设计研究与应用实践

目的 梳理和分析智能家居相关实验平台现状,探究智能家居综合实验平台的设计研究方法,对平台的构建展开应用实践。方法 以智能家居理论框架为基础,从传感器网络、数据、场景、被试等多个角度出发,对智能家居综合实验平台的设计方法和应用实践进行阐释。结果 提出智能家居综合实验平台中围绕“感知”“思考”“执行”3个层面的理论框架、应用实践研究方法和实践案例。结论 智能家居综合实验平台的理论构架对于智能家居领域的科研问题具有一定的理论影响力,3个层次在建设时相互独立,在理论中相互印证,在实践中相互支撑。建立智能家居综合实验平台,可以为智能家居及其相关领域的科研和产业问题提供实验场地、关键数据、核心算法等支撑,使相关研究可以在更完备、更集成及鲁棒性更强的框架下展开。智能家居综合实验平台的研究和实践整合了现有知识体系,从顶层设计、传感网络、数据研究、算法模型、用户研究、人机交互等多学科多领域交叉的角度为学术界和产业界提供参考,全面地推动智能家居领域的技术进步和设计创新。     

A fuzzy multi-criteria decision-making approach for managing performance and risk in integrated procurement–production planning

Nowadays in Supply Chain (SC) networks, a high level of risk comes from SC partners. An effective risk management process becomes as a consequence mandatory, especially at the tactical planning level. The aim of this article is to present a risk-oriented integrated procurement–production approach for tactical planning in a multi-echelon SC network involving multiple suppliers, multiple parallel manufacturing plants, multiple subcontractors and several customers. An originality of the work is to combine an analytical model allowing to build feasible scenarios and a multi-criteria approach for assessing these scenarios. The literature has mainly addressed the problem through cost or profit-based optimisation and seldom considers more qualitative yet important criteria linked to risk, like trust in the supplier, flexibility or resilience. Unlike the traditional approaches, we present a method evaluating each possible supply scenario through performance-based and risk-based decision criteria, involving both qualitative and quantitative factors, in order to clearly separate the performance of a scenario and the risk taken if it is adopted. Since the decision-maker often cannot provide crisp values for some critical data, fuzzy sets theory is suggested in order to model vague information based on subjective expertise. Fuzzy Technique for Order of Preference by Similarity to Ideal Solution is used to determine both the performance and risk measures correlated to each possible tactical plan. The applicability and tractability of the proposed approach is shown on an illustrative example and a sensitivity analysis is performed to investigate the influence of criteria weights on the selection of the procurement–production plan.     

Modelling the dispersion of flashing jets using CFD

Risk assessments related to industrial environments where gas is kept in liquid form under high pressure rely on the results from predictive tools. Computational Fluid Dynamics (CFD) is one such predictive tool and it is currently used for a range of applications. One of the most challenging application areas is the simulation of multiphase flows resulting from a breach or leakage in a pressurised pipeline or a vessel containing liquefied gas. The present paper deals with the modelling of the post-flashing scenario of a jet emanating from a circular orifice. In addition to being based on the equations governing fluid flow, the models used are those related to turbulence, droplet transport, evaporation, break-up and coalescence. Some of these models are semi-empirical and based on the data from applications other than flashing. However, these are the only models that are currently available in commercial codes and that would be used by consulting engineers for the type of modelling discussed above, namely the dispersion of a flashing release. A method for calculating inlet boundary conditions after flashing is also presented and issues related to such calculations are discussed. The results from a number of CFD based studies are compared with available experimental results. The results show that whilst a number of features of the experimental results can be reproduced by the CFD model, there are also a number of important shortcomings. The shortcomings are highlighted and discussed. Finally, an optimum approach to modelling of this type is suggested and methods to overcome modelling difficulties are proposed.     

Enterprise integration engineering reference framework and toolbox

Enterprise Integration Engineering (EIE) has emerged as an engineering discipline to re-structure the enterprise entities as integrated business processes that integrate human and technological resources to facilitate the knowledge sharing for better decision making. EIE is a complex task that requires applying different tools concerning strategic planning, performance management, modelling, simulation and business process management in order to properly engineer the enterprise entities. The present paper presents an EIE toolbox that aims to support enterprises in their decision making process and to provide different assisting tools to be applied on the components of the EIE Reference Framework proposed. Finally, a set of case studies are presented in order to demonstrate the utility of the EIE Reference Framework and its toolbox for strategic planning and enterprise decision making.     

Hybrid Petri-nets for modelling and performance evaluation of supply chains

Modelling and analysis of complex and co-ordinated supply chains is a crucial task due to its inherent complexity and uncertainty. Therefore, the current research direction is to devise an efficient modelling technique that maps the dynamics of a real life supply chain and assists industrial practitioners in evaluating and comparing their network with other competing networks. Here an effective modelling technique, the hybrid Petri-net, is proposed to efficiently handle the dynamic behaviour of the supply chain. This modelling methodology embeds two enticing features, i.e. cost and batch sizes, in deterministic and stochastic Petri-net for the modelling and performance evaluation of supply chain networks. The model is subsequently used for risk management to investigate the issues of supply chain vulnerability and risk that has become a major research subject in recent years. In the test bed, a simple productive supply chain and an industrial supply chain are modelled with fundamental inventory replenishment policy. Subsequently, its performance is evaluated along with the identification and assessment of risk factors using analytical and simulation techniques respectively. Thus, this paper presents a complete package for industrial practitioners to model, evaluate performance and manage risky events in a supply chain.     

Optimizing OEE,productivity and production cost for improving sales volume in an automobile industry through TPM: a case study

The aim of this paper is to investigate how increase in sales volume has evolved by improving overall equipment effectiveness (OEE) of machines, plant productivity and production cost through total productive maintenance (TPM) initiatives in a reputed tractors manufacturing industry in India. In the present scenario of global competitive market, the manufacturing industry needs to improve their operational performance for surviving and prospering. TPM is practised by industry as a business tool for rapid and continuous improvement in its manufacturing capabilities. OEE offers a powerful control tool to overcome production deficiencies and operational performance constrains. Productivity and manufacturing cost are also crucial operational measures to analyse the manufacturing performance. In this study, evaluation and analysis of the methodology adopted for improving sales volume through TPM initiatives was carried out using an interactive research approach. The industrial example on the application of OEE tool demonstrates that it has a remarkable potential to enhance the equipment effectiveness. The empirical findings of the study reveal that augmented OEE and productivity, and reduced production cost resulted to double the sales revenue and triple the profit within a period of three years. The industry also achieved notably tangible and intangible benefits with the TPM implementation.     

Exploring improvement trajectories with dynamic process cost modelling: a case from the steel industry

Improvement trajectories are sequential managed chains of improvement initiatives required to handle changes in competition and market. This paper presents a five-step framework, based on dynamic process cost modelling, which was developed during a four-year research project at a major stainless steel producer, to support the selection of an improvement trajectory based on strategic requirements to combine high product diversity with cost reduction. The framework aims to develop insight into what manufacturing capabilities are required to reach the strategic goals by combining system dynamics simulation with process cost modelling and visual exploratory data analysis in an iterative modelling procedure. The applicability of the five-step framework is demonstrated through a case study from the steel industry, in which a goal driven analysis is used to assess process requirements based on performance and market considerations.     

Synchronisation of inter-arrival times in manufacturing systems with main and side loops

Automated manufacturing systems commonly employ track-bound work piece transport mechanisms and work piece holders. In the systems considered, the track layout comprises one main loop and multiple side loops, following common industrial practice. As soon as work piece holders simultaneously traverse common tracks on multiple routes, e.g. because the main loop serves as a buffer, such manufacturing systems normally show complex, aperiodic inter-arrival times, which may affect performance. A synchronisation method is presented that limits the number of different inter-arrival times and controls the length of inter-arrival time periods without requiring extensive mathematical modelling. It is applied to a simplified model of a manufacturing system, for which allowable parameter tolerances are derived and validated with simulation. Since these tolerances are very narrow, synchronised operation requires continuous control of inter-arrival times. The applicability of the proposed approach is also demonstrated for a larger eight-station assembly model. Since the presented approach limits the number of system states reached, it helps the system designer anticipate and design against state explosions. The presented method clarifies the complexity—flexibility trade-off between system synchronisation and genuinely de-coupled designs that separate tracks for different routes.     

VPI-FP: an integrative information system for factory planning

Nowadays, one of the main challenges in factory planning is the consistent and coherent information modelling along planning processes. Despite the current efforts in the fields of virtual production as well as digital and virtual factory, planning and simulation applications mostly support only the analysis and the optimisation of single planning aspects. However, to match nowadays challenges, planners require solutions that provide an integrated view to evaluate planning scenarios in advance and to achieve increasing production quality and efficiency. The concept of virtual production intelligence (VPI) provides a basic concept for such an integrative information system that enables planners to integrate, to aggregate and to analyse data gathered during one planning project as well as to compare different projects. In this study, we present such an information system for factory planning using the concept of the VPI. The focus lies in particular on the information modelling as well as the information integration and evaluation. Therefore, the study presents theoretical basics and implementations of the VPI platform within a precise application scenario in factory planning. This is to process and provide a consolidated information base along the whole planning process to support factory planning projects.     

Organizing a virtual manufacturing enterprise: an analytic network process based approach for enterprise flexibility

Virtual manufacturing is a dynamic enterprise structure that will enable future competitiveness in the fast changing business environment. This is made possible through quick IT based integration of flexible and core competent business entities capable of providing value-added product and services. Flexibility elements represent change capabilities of enterprise wide processes and resources in time and cost dimensions. Value chain considerations require synergy among the participating flexible resources. Also decision information synchronization delays need to be managed so that other entity flow processes in the enterprise remain well synchronized. This may require a capability of dynamic changes in flexible structures leading to effective virtual enterprises. There is a need to develop suitable enterprise architectures for virtual enterprises that offer an increasing focus on agility. Infrastructure support for integration of flexible capability to attain synergy among resources is necessary for enterprise agility. We conceptualize virtual manufacturing (VM) as an integrating infrastructure of flexible resources made possible through alliance of enterprises that are individually core competent in specific business function. Such a VM can attain the required cost, flexibility and responsiveness characteristics in its operations to provide solution to the demanding customer in a global dynamic market. Modelling frameworks depicting these composite flexibility states have complex and tacit interrelationship with plural business goals. Analytical network process (ANP) has been used to model the interrelationship of different decision domains with a view to prioritize enterprise wide flexibility dimensions. The ANP modelling framework takes into consideration the interdependency among sub-strategies. We demonstrate through sensitivity analysis that strategic shift is required to accommodate changes due to dynamic condition in the business environment.     

Processes and measurement of knowledge management in supply chains: an integrative systematic literature review

During the last 10 years, important contributions about knowledge management (KM) issues in supply chain management (SCM) have been published. The current paper aims to build upon previous literature reviews focused on KM in supply chains (SCs) from an integrative perspective, particularly recognising the studies conducted by Bhosale and Kant (2016. “Metadata Analysis of Knowledge Management in Supply Chain: Investigating the Past and Predicting the Future.” Business Process Management Journal 22 (1): 140–172) and Cerchione and Esposito (2016. “A Systematic Review of Supply Chain Knowledge Management Research: State of the Art and Research Opportunities.” International Journal of Production Economics 182: 276–292) as an effort to discuss the evolution of KM in the SC field. To this end, a systematic literature review including 210 papers is conducted over the period 2008–2017 from three positions previously not addressed jointly within the supply chain (SC) context: research methods employed by the authors; KM processes applied in the business processes across the SC; and intra and inter- organisational performance metrics linked with KM initiatives. Results exhibited that: (i) ‘Survey’ and ‘Case study’ are the two research methodologies mostly employed by authors (ii) the knowledge transfer is discussed in the majority of the studies reviewed, (iii) 114 intra and inter-organisational performance metrics are reported within the SC context from an empirical data approach. Findings concerning previous identified gap analysis and future lines of research are described.     

An integrated ISM fuzzy MICMAC approach for modelling the supply chain knowledge flow enablers

The aim of this study is to identify supply chain knowledge flow enablers (SCKFEs) to inspect interrelationships among these enablers and classify these enablers into driving power and dependence power using an integrated interpretive structural modelling (ISM) and fuzzy Matriced Impacts Croisés Multiplication Appliquée á un Classement (MICMAC) methodology. While the ISM methodology analyses the interactions among the SCKFEs, fuzzy MICMAC analysis is employed to obtain insights into the dependencies among the SCKFEs. A total of 34 SCKFEs were identified through the literature review and expert opinion. As an example, an Indian manufacturing organisation is selected that is willing to adopt the successful knowledge flow for improving supply chain (SC) performance to overcome the intense competition among the SC versus SC. The research shows SCKFEs having high driving power and low dependence have strategic importance because of their driving nature, while the SCKFEs having high dependence and low driving power are more performance orientated. Therefore, it is the responsibility of SC executives to address the high driving power SCKFEs for the enhancement of SC performance. This categorisation provides a useful tool to top management to differentiate between independent and dependent SCKFEs and their mutual relationships, helping them focus on those key SCKFEs that are most significant. This gives a clear picture to SC practitioners and decision-makers about number of SCKFEs, interrelationship and dependencies existing among them.     

Investigating replenishment policies for centralised and decentralised supply chains using stochastic programming approach

In this paper, a multiple period replenishment problem based on (s, S) policy is investigated for a supply chain (SC) comprising one retailer and one manufacturer with uncertain demand. Novel mixed-integer linear programming (MILP) models are developed for centralised and decentralised decision-making modes using two-stage stochastic programming. To compare these decision-making modes, a Monte Carlo simulation is applied to the optimization models’ policies. To deal with demand uncertainty, scenarios are generated using Latin Hypercube Sampling method and their number is reduced by a scenario reduction technique. In large test problems, where CPLEX solver is not able to reach an optimal solution in the centralised model, evolutionary strategies (ES) and imperialist competitive algorithm (ICA) are applied to find near optimal solutions. Sensitivity analysis is conducted to show the performance of the proposed mathematical models. Moreover, it is demonstrated that both ES and ICA provide acceptable solutions compared to the exact solutions of the MILP model. Finally, the main parameters affecting difference between profits of centralised and decentralised SCs are investigated using the simulation method.     

All-optical router with pulse-position modulation header processing in high-speed photonic packet switching networks

In future high-speed photonic packet switching networks, it is highly desirable to carry out robust alloptical header recognition to provide high-throughput routing. The authors present a pulse-position modulation header processing (PPM-HP) scheme, offering significantly reduced routing table size and employing a single bitwise AND operation to carry out correlation of the packet header with the entire routing table entries. The downsized routing table also offers multiple transmission modes (unicast, multicast and broadcast) in the optical layer and improves core network scalability where the number of core/edge nodes could be altered without the need for changing the number of routing table entries. The authors present modelling and simulation of the packet switching router based on PPM-HP. Noise propagation and crosstalk incurred in a multiple-hop routing scenario are investigated. The simulation results are presented and compared with the theoretical calculations.     

The industrial management of SMEs in the era of Industry 4.0

Industry 4.0 provides new paradigms for the industrial management of SMEs. Supported by a growing number of new technologies, this concept appears more flexible and less expensive than traditional enterprise information systems such as ERP and MES. However, SMEs find themselves ill-equipped to face these new possibilities regarding their production planning and control functions. This paper presents a literature review of existing applied research covering different Industry 4.0 issues with regard to SMEs. Papers are classified according to a new framework which allows identification of the targeted performance objectives, the required managerial capacities and the selected group of technologies for each selected case. Our results show that SMEs do not exploit all the resources for implementing Industry 4.0 and often limit themselves to the adoption of Cloud Computing and the Internet of Things. Likewise, SMEs seem to have adopted Industry 4.0 concepts only for monitoring industrial processes and there is still absence of real applications in the field of production planning. Finally, our literature review shows that reported Industry 4.0 projects in SMEs remained cost-driven initiatives and there in still no evidence of real business model transformation at this time.     

AGV controlled FMS

One of the key factors that prevent the implementation of Flexible Manufacturing Systems (FMS) is the elaborate cost associated with the control software. In a FMS there is often a wide range of equipment, such as personal computers, Programmable Logical Controllers (PLCs), CNC Machines or robots, each of these having their own 'intelligence' and library of data. Providing a means of communication between these individual controllers has traditionally been achieved using a Local Area Network (LAN). This proves more expensive when traditional manual operated machines have to be integrated into the system. The model described in this paper provides an alternative to the conventional use of a LAN in a FMS environment. In the design solution, an Automatically Guided Vehicle (AGV) is used as both the materials handling unit and the communications line linking each station to the host controller. Communications between the AGV and peripheral equipment is achieved using a standard infrared data link, eliminating hard-wiring and network protocols. A simulation model has been developed to demonstrate the feasibility of such a system, using industrial data. The software package Witness is used to develop the simulation model. The objective from developing this simulation model is to test whether an AGV is capable of meeting the demands of such a scenario. The research undertaken aims to test this by modelling an existing factory layout. Using this layout and captured machining times and part routes, from the factory database, the feasibility of such AGV controlled production system is established. The model shows that such a system is plausible in a scenario where machine times are high and the distance between machines is large.     

Blockchain-oriented dynamic modelling of smart contract design and execution in the supply chain

Recently, the applications of Blockchain technology have begun to revolutionise different aspects of supply chain (SC) management. Among others, Blockchain is a platform to execute the smart contracts in the SC as transactions. We develop and test a new model for smart contract design in the SC with multiple logistics service providers and show that this problem can be presented as a multi-processor flexible flow shop scheduling. A distinctive feature of our approach is that the execution of physical operations is modelled inside the start and completion of cyber information services. We name this modelling concept ‘virtual operation’. The constructed model and the developed experimental environment constitute an event-driven dynamic approach to task and service composition when designing the smart contract. Our approach is also of value when considering the contract execution stage. The use of state control variables in our model allows for operations status updates in the Blockchain that in turn, feeds automated information feedbacks, disruption detection and control of contract execution. The latter launches the re-scheduling procedure, comprehensively combining planning and adaptation decisions within a unified methodological framework of dynamic control theory. The modelling complex developed can be used to design and control smart contracts in the SC.