60 resultados para Location Manufacturing Decision


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The forces of globalisation now impacting on local economies pose threats to the existing paradigm of competences and routines, yet simultaneously offer opportunities to integrate new knowledge and learning. This is particularly pertinent with respect to Europe’s ‘mature regions’, which are undergoing a major economic restructuring by trying to shift from traditional manufacturing activities to hybrid activities that comprise a combination of manufacturing and a higher component of intangible inputs and related knowledge service activities. The objective of the article is to discuss the concept of ‘place leadership’ by looking at how the embedded skills, knowledge and cumulated learning of a place can be used by its institutional infrastructure to identify sustainable growth trajectories. In other words, its aim is to explore how the economic, social, institutional and cultural aspects of places shape the opportunities for upgrading and renovation drawing upon their historical specialisation. The conceptual contribution of the article draws on two case studies, in the West Midlands, UK and in Prato, Tuscany, where we study the processes of decision-making, forms of leadership and ultimately the nature of local leadership.

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Purpose: This paper aims to explore practices and technologies successfully servitised manufacturers employ in the delivery of advanced services. Design/methodology/approach: A case study methodology is applied across four manufacturing organisations successful in servitization. Through interviews with personnel across host manufacturers, their partners, and key customers, extensive data are collected about service delivery systems. Analyses identify convergence in their practices and technologies. Findings: Six distinct technologies and practices are revealed: facilities and their location, micro-vertical integration and supplier relationships, information and communication technologies (ICTs), performance measurement and value demonstration, people deployment and their skills, and business processes and customer relationships. These are then combined in an integrative framework that illustrates how operations are configured to successfully deliver advanced services. Research limitations/implications: The analyses are reductive and rationalising. Future studies could identify other technologies and practices. Case study as a method is inherently limited in the extent to which findings can be generalised. Practical implications: Awareness and interest in servitization is growing, yet adoption of a servitization strategy requires particular organisational capabilities on the part of the manufacturer. This study identifies technologies and practices that underpin these capabilities. Originality/value: This paper contributes to the understanding of the servitization process and, in particular, the implications to broader operations of the firm. © Emerald Group Publishing Limited.

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The purpose of this paper is to delineate a green supply chain (GSC) performance measurement framework using an intra-organisational collaborative decision-making (CDM) approach. A fuzzy analytic network process (ANP)-based green-balanced scorecard (GrBSc) has been used within the CDM approach to assist in arriving at a consistent, accurate and timely data flow across all cross-functional areas of a business. A green causal relationship is established and linked to the fuzzy ANP approach. The causal relationship involves organisational commitment, eco-design, GSC process, social performance and sustainable performance constructs. Sub-constructs and sub-sub-constructs are also identified and linked to the causal relationship to form a network. The fuzzy ANP approach suitably handles the vagueness of the linguistics information of the CDM approach. The CDM approach is implemented in a UK-based carpet-manufacturing firm. The performance measurement approach, in addition to the traditional financial performance and accounting measures, aids in firms decision-making with regard to the overall organisational goals. The implemented approach assists the firm in identifying further requirements of the collaborative data across the supply-cain and information about customers and markets. Overall, the CDM-based GrBSc approach assists managers in deciding if the suppliers performances meet the industry and environment standards with effective human resource. © 2013 Taylor & Francis.

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We describe a novel and potentially important tool for candidate subunit vaccine selection through in silico reverse-vaccinology. A set of Bayesian networks able to make individual predictions for specific subcellular locations is implemented in three pipelines with different architectures: a parallel implementation with a confidence level-based decision engine and two serial implementations with a hierarchical decision structure, one initially rooted by prediction between membrane types and another rooted by soluble versus membrane prediction. The parallel pipeline outperformed the serial pipeline, but took twice as long to execute. The soluble-rooted serial pipeline outperformed the membrane-rooted predictor. Assessment using genomic test sets was more equivocal, as many more predictions are made by the parallel pipeline, yet the serial pipeline identifies 22 more of the 74 proteins of known location.

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Four bar mechanisms are basic components of many important mechanical devices. The kinematic synthesis of four bar mechanisms is a difficult design problem. A novel method that combines the genetic programming and decision tree learning methods is presented. We give a structural description for the class of mechanisms that produce desired coupler curves. Constructive induction is used to find and characterize feasible regions of the design space. Decision trees constitute the learning engine, and the new features are created by genetic programming.

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Due to vigorous globalisation and product proliferation in recent years, more waste has been produced by the soaring manufacturing activities. This has contributed to the significant need for an efficient waste management system to ensure, with all efforts, the waste is properly treated for recycling or disposed. This paper presents a Decision Support System (DSS) framework, based on Constraint Logic Programming (CLP), for the collection management of industrial waste (of all kinds) and discusses the potential employment of Radio-Frequency Identification Technology (RFID) to improve several critical procedures involved in managing waste collection. This paper also demonstrates a widely distributed and semi-structured network of waste producing enterprises (e.g. manufacturers) and waste processing enterprises (i.e. waste recycling/treatment stations) improving their operations planning by means of using the proposed DSS. The potential RFID applications to update and validate information in a continuous manner to bring value-added benefits to the waste collection business are also presented. © 2012 Inderscience Enterprises Ltd.

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This paper examines the determinants of a multinational enterprise’s (MNEs) decision to invest in countries classified as tax havens. To the best of our knowledge this has not been analysed at the cross-country level before. We use the ownership-location-internalisation (OLI) paradigm and link it with financial specific advantages to develop a number of hypotheses which are subsequently tested by our empirical model. Our analysis is based on a large firm-level database covering 39,543 MNEs across the world for the period 2002- 2011. We find that higher corporate taxes faced by MNEs at home increase the likelihood of locating in a tax haven. Moreover, high technology manufacturing and services MNEs that possess large levels of intangible assets are also more likely to locate subsidiaries in tax havens. Finally, we find evidence that MNEs from countries with a more coordinated market orientation are less likely to locate in tax havens.

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Rework strategies that involve different checking points as well as rework times can be applied into reconfigurable manufacturing system (RMS) with certain constraints, and effective rework strategy can significantly improve the mission reliability of manufacturing process. The mission reliability of process is a measurement of production ability of RMS, which serves as an integrated performance indicator of the production process under specified technical constraints, including time, cost and quality. To quantitatively characterize the mission reliability and basic reliability of RMS under different rework strategies, rework model of RMS was established based on the method of Logistic regression. Firstly, the functional relationship between capability and work load of manufacturing process was studied through statistically analyzing a large number of historical data obtained in actual machining processes. Secondly, the output, mission reliability and unit cost in different rework paths were calculated and taken as the decision variables based on different input quantities and the rework model mentioned above. Thirdly, optimal rework strategies for different input quantities were determined by calculating the weighted decision values and analyzing advantages and disadvantages of each rework strategy. At last, case application were demonstrated to prove the efficiency of the proposed method.

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This paper presents a new, dynamic feature representation method for high value parts consisting of complex and intersecting features. The method first extracts features from the CAD model of a complex part. Then the dynamic status of each feature is established between various operations to be carried out during the whole manufacturing process. Each manufacturing and verification operation can be planned and optimized using the real conditions of a feature, thus enhancing accuracy, traceability and process control. The dynamic feature representation is complementary to the design models used as underlining basis in current CAD/CAM and decision support systems. © 2012 CIRP.

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This paper describes the application of a model, initially developed for determining the e-business requirements of a manufacturing organization, to assess the impact of management concerns on the functions generated. The model has been tested on 13 case studies in small, medium and large organizations. This research shows that the incorporation of concerns for generating the requirements for e-business functions improves the results, because they expose issues that are of relevance to the decision making process relating to e-business. Running the model with both and without concerns, and then presenting the reasons for major variances, can expose the issues and enable them to be studied in detail at the individual function/ reason level. © IFIP International Federation for Information Processing 2013.

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Purpose - The purpose of this paper is to report an investigation of local sustainable production in Australia and Sweden aimed at exploring the factors contributing to survival and competitiveness of manufacturing companies. Design/methodology/approach - In Australia, six companies were studied in 2010, with comparisons being made with three of them from earlier projects. In Sweden, eight manufacturing companies were studied on two occasions 30 years apart, in 1980 and 2010. To provide a valid comparative perspective a common format for data collection and analysis was used. Findings - There has been a shift in the nature of competition in both Sweden and Australia due to an increasing complexity of the global business environment as well as changes in technology and customer expectations. Despite the differences in country context, the findings suggest that all the manufacturing companies have a good awareness of the elements of the market environment and the relationships with their competitive strategy. However, in general, the Swedish companies have more experience of managing the risks and benefits from operating in the international environment. Research limitations/implications - The results of the research are based on a relatively small sample of case companies in a limited number of industrial sectors. There are methodology implications for future research in the area. Practical implications - The research results have practical implications for the manufacturing industry, especially for companies operating in a competitive international environment. Originality/value - The paper is based on original case research and comparative analysis of data from different geographical contexts. It contributes to both theory and management practice about the strategic resources, decision choices, competitive environments and firm values needed to address external market demands as well as in building internal capabilities.

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Floods are one of the most dangerous and common disasters worldwide, and these disasters are closely linked to the geography of the affected area. As a result, several papers in the academic field of humanitarian logistics have incorporated the use of Geographical Information Systems (GIS) for disaster management. However, most of the contributions in the literature are using these systems for network analysis and display, with just a few papers exploiting the capabilities of GIS to improve planning and preparedness. To show the capabilities of GIS for disaster management, this paper uses raster GIS to analyse potential flooding scenarios and provide input to an optimisation model. The combination is applied to two real-world floods in Mexico to evaluate the value of incorporating GIS for disaster planning. The results provide evidence that including GIS analysis for a decision-making tool in disaster management can improve the outcome of disaster operations by reducing the number of facilities used at risk of flooding. Empirical results imply the importance of the integration of advanced remote sensing images and GIS for future systems in humanitarian logistics.

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Climate change has become one of the most challenging issues facing the world. Chinese government has realized the importance of energy conservation and prevention of the climate changes for sustainable development of China's economy and set targets for CO2 emissions reduction in China. In China industry contributes 84.2% of the total CO2 emissions, especially manufacturing industries. Data envelopment analysis (DEA) and Malmquist productivity (MP) index are the widely used mathematical techniques to address the relative efficiency and productivity of a group of homogenous decision making units, e.g. industries or countries. However, in many real applications, especially those related to energy efficiency, there are often undesirable outputs, e.g. the pollutions, waste and CO2 emissions, which are produced inevitably with desirable outputs in the production. This paper introduces a novel Malmquist-Luenberger productivity (MLP) index based on directional distance function (DDF) to address the issue of productivity evolution of DMUs in the presence of undesirable outputs. The new RAM (Range-adjusted measure)-based global MLP index has been applied to evaluate CO2 emissions reduction in Chinese light manufacturing industries. Recommendations for policy makers have been discussed.

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Objective: The Any Qualified Provider framework in the National Health Service has changed the way adult audiology services are offered in England. Under the new rules, patients are being offered a choice in geographical location and audiology provider. This study aimed to explore how choices in treatment are presented and to identify what information patients need when they are seeking help with hearing loss. Design: This study adopted qualitative methods of ethnographic observations and focus group interviews to identify information needed prior to, and during, help-seeking. Observational data and focus group data were analysed using the constant comparison method of grounded theory. Study sample: Participants were recruited from a community Health and Social Care Trust in the west of England. This service incorporates both an Audiology and a Hearing Therapy service. Twenty seven participants were involved in focus groups or interviews. Results: Participants receive little information beyond the detail of hearing aids. Participants report little information that was not directly related to uptake of hearing aids. Conclusions: Participant preferences were not explored and limited information resulted in decisions that were clinician-led. The gaps in information reflect previous data on clinician communication and highlight the need for consistent information on a range of interventions to manage hearing loss.

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From 1992 to 2012 4.4 billion people were affected by disasters with almost 2 trillion USD in damages and 1.3 million people killed worldwide. The increasing threat of disasters stresses the need to provide solutions for the challenges faced by disaster managers, such as the logistical deployment of resources required to provide relief to victims. The location of emergency facilities, stock prepositioning, evacuation, inventory management, resource allocation, and relief distribution have been identified to directly impact the relief provided to victims during the disaster. Managing appropriately these factors is critical to reduce suffering. Disaster management commonly attracts several organisations working alongside each other and sharing resources to cope with the emergency. Coordinating these agencies is a complex task but there is little research considering multiple organisations, and none actually optimising the number of actors required to avoid shortages and convergence. The aim of the this research is to develop a system for disaster management based on a combination of optimisation techniques and geographical information systems (GIS) to aid multi-organisational decision-making. An integrated decision system was created comprising a cartographic model implemented in GIS to discard floodable facilities, combined with two models focused on optimising the decisions regarding location of emergency facilities, stock prepositioning, the allocation of resources and relief distribution, along with the number of actors required to perform these activities. Three in-depth case studies in Mexico were studied gathering information from different organisations. The cartographic model proved to reduce the risk to select unsuitable facilities. The preparedness and response models showed the capacity to optimise the decisions and the number of organisations required for logistical activities, pointing towards an excess of actors involved in all cases. The system as a whole demonstrated its capacity to provide integrated support for disaster preparedness and response, along with the existence of room for improvement for Mexican organisations in flood management.