Optimal design and augmentation of strongly attack-tolerant two-hop clusters in directed networks

We consider the problems of minimum-cost design and augmentation of directed network clusters that have diameter 2 and maintain the same diameter after the deletion of up to R elements (nodes or arcs) anywhere in the cluster. The property of a network to maintain not only the overall connectivity, but also the same diameter after the deletion of multiple nodes/arcs is referred to as strong attack tolerance. This paper presents the proof of NP-completeness of the decision version of the problem, derives tight theoretical bounds, as well as develops a heuristic algorithm for the considered problems, which are extremely challenging to solve to optimality even for small networks. Computational experiments suggest that the proposed heuristic algorithm does identify high-quality near-optimal solutions; moreover, in the special case of undirected networks with identical arc construction costs, the algorithm provably produces an exact optimal solution to strongly attack-tolerant two-hop network design problem, regardless of the network size.     

Genetic algorithm to production planning and scheduling problems for manufacturing systems

Fundamental and extended multi-objective (MO) models are designed to address earliness/tardiness production scheduling planning (ETPSP) problems with multi-process capacity balance, multi-product production and lot-size consideration. A canonical genetic algorithm (GA) approach and a prospective multi-objective GA (MOGA) approach are proposed as solutions for different practical problems. Simulation results as well as comparisons with other techniques demonstrate the effectiveness of the MOGA approach, which is a noted improvement to any of the existing techniques, and also in practice provides a new trend of integrating manufacturing resource planning (MRPII) with just-in-time (JIT) in the production planning procedure.     

The permutation flow shop problem with just in time production considerations

This research presents a variation to the permutation flow shop problem where Just In Time (JIT) production requirements are taken into account. The model developed in this research employs dual objectives. In addition to the traditional objective of minimizing the production makespan, minimization of Miltenburg's material usage rate is also incorporated. In this model, multiple units of any product are permitted in the production sequence. However, the minimization of material usage rates attempts to prevent batch scheduling of products and allows unit flow of products as required in demand flow manufacturing. A solution method is proposed for determining an optimal production sequence via an efficient frontier approach and Simulated Annealing (SA). Test problems and specific performance criteria are used to assess the solutions generated by the proposed method. Experimental results presented in this paper show that the use of the efficient frontier and SA provide solutions that approach the optimal solution for the performance measures used in this research.     

New MNE subsidiaries in old clusters: when,why, and how

Despite the rise of globalization, industrial clusters remain vibrant spaces for the generation of knowledge and innovation. Aware of this reality, multinational enterprises (MNEs) seek to reconcile the advantages of international operations with the specific endowments of individual territories. By studying the case of the Inditex subsidiary in the Vinalopó footwear cluster, this research shows how the creation and activity of a specialized subsidiary and the evolution of the industrial system interweave. The study shows that, rather than agglomeration per se, access to specific resources guides location as the cluster matures. Furthermore, local embeddedness shapes post-entry dynamics at the micro and meso levels. Autonomous decisions boost the subsidiary’s access to local networks and the exploitation of cluster advantages, aiding the resilience of the cluster by contributing extra-cluster knowledge.     

基于混合分布的中国股票波动风险因素的识别与分析

论文用GARCH模型描述股票的波动特性，应用混合分布对中国上市公司按照股票波动特性进行分组，发现中国上市公司的波动特性可以被分为4个子总体。其中，子总体1主要包含表现异常的公司股票，其他三个子总体的参数向量的相关性相似，风险大小不同。应用列联表法分析和多元logistic模型统计分析发现，非国有股权分散公司、制造业公司相对偏向低风险公司，社会服务业、房地产公司相对偏向高风险公司，制造业的公司（股票）波动的持续性相对较低。混合分布是对股票特性进行分组的良好工具。     

From blind spots to hotspots: How knowledge services clusters develop and attract foreign investment

This paper explores local and global dynamics underlying the development of knowledge services clusters, which we define as new geographic concentrations of technical talent and service providers offering upstream technical and knowledge-intensive business services to regional and global clients. Taking a co-evolutionary perspective on the development of knowledge services clusters in Latin America, based on data from the Offshoring Research Network (ORN), we find that cluster growth results from intersecting trajectories: the emergence of local talent pools and capabilities initially serving local and regional demand; broadening global search for talent and expertise by multinational corporations; and internationalization strategies of service providers competing to serve global clients. Findings suggest that increasing commoditization of knowledge services opens up windows of opportunity for new clusters, but also involves challenges for sustainable growth. Results may stimulate future research on global sourcing and cluster development.     

Quality management and performance: a comparison between the UK and Turkey

Purpose: The aim of this article is to detail the correlation between quality management, specifically its tools and critical success factors, and performance in terms of primary operational and secondary organisational performances.

Design/methodology/approach: Survey data from the UK and Turkey were analysed using exploratory factor analyses, structural equation modelling and regression analysis.

Findings: The results show that quality management has a significant and positive impact on both primary and secondary performances; that Turkish and UK attitudes to quality management are similar; and that quality management is widely practised in manufacturing and service industries but has more statistical emphasis in the manufacturing sector. The main challenge for making quality management practice more effective lies in an appropriate balanced use of the different sorts of the tools and critical success factors.

Originality/value: This study takes a novel approach by: (i) exploring the relationship between primary operational and secondary organisational performances, (ii) using service and manufacturing data and (iii) making a cross-country comparison between the UK (a developed economy) and Turkey (a developing economy).

Limitations: Detailed contrast provided between only two countries.     

Responding to discontinuities in product-based service supply chains in the COVID-19 pandemic: Towards transilience

PurposeIn this study, we identify and characterise how organisations have responded, in ways ranging from restoration to radical change, to discontinuities in their product-based service (PBS) supply chains during the COVID-19 pandemic.Design/methodology/approachFollowing a theoretical approach that integrates transilience and panarchy theory as a response strategy in PBS supply chains, our qualitative study involved collecting data through 19 semi-structured interviews at six manufacturing firms during the first 6 months of the COVID-19 pandemic (i.e., March to August 2020) and triangulating the findings with the secondary data and that from an industry workshop. Following an inductive approach, we performed thematic data analysis in Nvivo software package.FindingsThe findings suggest characterising discontinuities in PBS supply chains as unmanageable external supply-side, demand-side or interactional discontinuities or other manageable deliberate or forced organisational discontinuities. Following that characterisation, we developed a conceptual framework combing both resilience and transformation into new service opportunities.Research limitations/implicationsWe gained insights into the first-response abilities and ways of coping among manufacturing firms during the COVID-19 pandemic. Though our findings capture a contemporary, eye-of-the-storm perspective on future directions, a longitudinal study on the pandemic could further validate and extend the modes of response that complement mitigation with the ability to accelerate change or innovation of internal process or external service offerings.Originality/valueCombining current literature with lessons learned from the firms' immediate responses, this paper's overview and characterisation of discontinuities following the COVID-19 outbreak in PBS supply chains demonstrate how manufacturing firms can foster transilience. As such, it integrates product-based supply chain discontinuities into the domain of service-based supply chains.     

ON EXTENSIONS OF PROBABILISTIC PROFIT BUDGETS: A COMMENT

Recognizing the potential importance of new uses of analysis, the author provides an alternative approach for constructing the confidence interval (C.I.) for the population coefficient of variation, V=α/μ. More specifically, the comment demonstrates the use of some of the existing percentage points of the sample coefficient of variation, v=s/x . The results of these approximations are then compared empirically with the results recently published by Hayya, Copeland and Chan [1, pp. 115–118]. The available approximations given by Iglewicz [2] and again by Iglewicz and Myers [3] of the practical range of V and of the sample size n are more accurate than those obtained using the method in [1].     

Tardiness heuristic for scheduling Flexible Manufacturing Systems

Abstract

This paper evaluates the tardiness performance of a sampling-based adaptive heuristic in a dynamic manufacturing environment. A test bed, following a real world manufacturing system, has been developed. The proposed algorithm has been implemented in this simulated environment. After fine tuning the algorithm, it has been tested in various shop conditions. The results of these simulation studies are summarized.     

Flexible reasoning using sensible agent-based systems: A case study in job flow scheduling

Planning and control systems for highly dynamic and uncertain manufacturing environments require adaptive flexibility and decision-making capabilities. Modern distributed manufacturing systems assess the utility of planning and executing solutions for both system goals (e.g. minimize manufacturing production time for all parts or minimize WIP) and local goals (e.g. expedite part A production schedule or maximize machine X utilization). Sensible Agents have the ability to alter their autonomy levels to choose among a set of decision models in order to handle the differences between local and system goals. In this paper, Sensible Agents are applied to a production planning and control problem in the context of job shop scheduling and decision model theory. Sensible Agents provide for trade-off reasoning mechanisms among system and local utilities that are flexible and responsive to an agent's abilities, situational context and position in the organizational structure of the system.     

Cloud platforms for remote monitoring system: a comparative case study

Abstract

Currently, industrial companies are increasingly introducing services to extend their tangible products. Remote monitoring solutions are one of the most implemented services by machine builders to manage their relationship with customers and also improve their business performance in the digital manufacturing era. However, the conventional method of remote monitoring cannot fulfill distributed business environments. Therefore, new solutions are needed to enable remote connection in manufacturing. By reviewing recent literature and proposing new features for software which can be used for remote service and operations, this research paper introduces a remote monitoring system connecting into a central cloud-based system with edge computing network architecture, namely Cloud-based Remote Monitoring (CloudRM). This proposed CloudRM also has been implemented in two different case companies for analysis and evaluation from a value proposition and technical implementation point of view. It shows significant improvement in production management and measurement by using CloudRM.     

Coordinated Contract Decisions in a Make‐to‐Order Manufacturing Supply Chain: A Stochastic Programming Approach

One of the important objectives of supply chain S&OP (Sales and Operations Planning) is the profitable alignment of customer demand with supply chain capabilities through the coordinated planning of sales, production, distribution, and procurement. In the make‐to‐order manufacturing context considered in this paper, sales plans cover both contract and spot sales, and procurement plans require the selection of supplier contracts. S&OP decisions also involve the allocation of capacity to support sales plans. This article studies the coordinated contract selection and capacity allocation problem, in a three‐tier manufacturing supply chain, with the objective to maximize the manufacturer's profitability. Using a modeling approach based on stochastic programming with recourse, we show how these S&OP decisions can be made taking into account economic, market, supply, and system uncertainties. The research is based on a real business case in the Oriented Strand Board (OSB) industry. The computational results show that the proposed approach provides realistic and robust solutions. For the case considered, the planning method elaborated yields significant performance improvements over the solutions obtained from the mixed integer programming model previously suggested for S&OP.     

供应链管理对于大型复杂产品制造业集群演进的影响机理研究

产业集群演进是指在一定驱动力下产业集群从某个具有阶段特征的整体结构与态势向另一个具有阶段特征的结构与态势转变发展的过程。在这个过程中供应链管理可以促进资源的有效整合和利用,优化产业结构,促进产业升级。在前人关于大型复杂产品和供应链管理相关研究基础上,以组织要素、产品复杂性要素、产业关联度要素为影响变量,构建了供应链管理对大型复杂产品制造业集群演进的影响机理模型,通过实证分析,得出SCM对于大型复杂产品制造业集群演进的影响机理是一个全方位的作用模式,这为大型复杂产品制造业集群中供应链管理提供了借鉴。     

Measuring exposure to bullying at work: The validity and advantages of the latent class cluster approach

Abstract

This paper addresses the construct and predictive validity of two methods for classifying respondents as victims of workplace bullying. Although bullying is conceived as a complex phenomenon, the dominant method used in bullying surveys, the operational classification method, only distinguishes two groups: victims versus non-victims. Hence, the complex nature of workplace bullying may not be accounted for. Therefore a latent class cluster approach is suggested to model the data, which was obtained by using the Negative Acts Questionnaire (NAQ) administered to employees in Belgium (n=6,175). Latent class modelling is a method of analysis that does not appear to have been used in occupational health psychology before. In this study, six latent classes emerged: “not bullied,” “limited work criticism,” “limited negative encounters,” “sometimes bullied,” “work related bullied,” and “victims.” The results show that compared to the traditional operational classification method, the latent class cluster approach shows higher construct and higher predictive validity with respect to self-assessments and indicators of strain and well-being at work. The consequences of these results for theory, future research, and practice are discussed.     

Determination of the optimal number of kanbans and kanban allocation in a FMS: A simulationbased study

A simulation-based study is presented to compare the performance of a set of kanban allocation rules in a flexible manufacturing system (FMS) operating in a pull mode. This paper also presents a simulation-based direct search approach to determine the optimal number of kanbans and their simultaneous allocation to different part types. This paper presents a realistic cost function that includes a penalty for failing to meet the demand on time, and a penalty for rescheduling delivery of materials from vendors. The model captures limited flexibility in the form of operational flexibility in a FMS. Future extensions to this study are discussed.     

A finite capacity material requirements planning system

In a discrete parts manufacturing environment, material requirement planning (MRP) is carried out without considering the manufacturing resource capacity. As a result, during implementation, adjustments in planned orders may become necessary. This paper presents a finite capacity material requirements planning algorithm (FCMRP) to obtain capacity-based production plans. These plans need no costly adjustments to satisfy the capacity constraints. Performance of the FCMRP system, when studied through a set of test examples, has been found to be superior to the existing MRP system.     

A simulated annealing algorithm for designing cellular manufacturing systems with productivity consideration

In this paper, we propose a productivity model for solving the machine-part grouping problem in cellular manufacturing (CM) systems. First, a non-linear 0-1 integer programming model is developed to identify machine groups and part families simultaneously. This model aims to maximize the system productivity defined as the ratio of total output to the total material handling cost. Second, an efficient simulated annealing (SA) algorithm is developed to solve large-scale problems. This algorithm provides several advantages over the existing algorithms. It forms part families and machine cells simultaneously. It also considers production volume, sales price, and maximum number of machines in each cell and total material handling cost. The proposed SA also has the ability to determine the optimum number of manufacturing cells. The performance of the developed models is tested on eight problems of different size and complexity selected from the literature. The results show the superiority of the SA algorithm over the mathematical programming model in both productivity and computational time.     

Kanban optimization by simulation and evolution

The problem of the optimal design of multistage systems with Kanban control mechanism is investigated. The optimization problem generalizes those from literature by considering a general criterion function and including the lot sizes as decision variables. Since no analytical solutions can be expected simulation combined with a genetic algorithm is used. The simulator KaSimIR as well as the optimization tool LEO are briefly described. Some examples demonstrate the usability of the approach.     

An integrated lean and green approach for improving sustainability performance: a case study of a packaging manufacturing SME in the U.K.

Abstract

Competitive landscape, informed consumers and stringent regulations have forced many manufacturing small- and medium-sized enterprises (SMEs) to focus on operational efficiency along with sustainability issues in recent years. While many manufacturing organisations have been taking lean initiatives for the past few years for operational excellence, an impulsive rush to adopt lean without a strategic deployment vision has led to scattered implementation of lean tools and projects without desired success. Many researchers and practitioners prescribe value stream mapping as a foundation for lean transformation initiatives; however, little empirical work is available on the symbiosis of lean and green paradigms to reap maximum benefits. This research, through a systematic methodology and a novel tool called Green Integrated Value Stream Mapping (GIVSM), integrates both paradigms in a case study on a U.K. packaging-manufacturing SME. Applying the GIVSM demonstrates that simultaneous deployment of lean and green paradigms have synergistic effect for improving both operational efficiency and environmental performance. In addition, continuous improvement framework with sustainable procurement is proposed to overcome the lean-green misalignments. This study also provides a guiding reference for practitioners to undertake similar improvement projects and identifies opportunities to expand this academic research on integrated lean-green approach into other industry sectors.