985 resultados para manufacturing flexibility


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Increasing awareness of the benefits of stimulating entrepreneurial behaviour in small and medium enterprises has fostered strong interest in innovation programs. Recently many western countries have invested in design innovation for better firm performance. This research presents some early findings from a study of companies that participated in a holistic approach to design innovation, where the outcomes include better business performance and better market positioning in global markets. Preliminary findings from in-depth semi-structured interviews indicate the importance of firm openness to new ways of working and to developing new processes of strategic entrepreneurship. Implications for theory and practice are discussed.

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The project investigated the relationships between diversification in modes ofdelivery, use of information and communication technologies, academics’ teaching practices, and the context in which those practices are employed, in two of the three large universities in Brisbane—Griffith University and the Queensland University of Technology (QUT). The project’s initial plan involved the investigation of two sites: Queensland University of Technology’s Faculty of Education (Kelvin Grove campus) and Griffith University’s Faculty of Humanities(Nathan campus). Interviews associated with the Faculty of Education led to a decision to include a third site—the School of Law within Queensland University of Technology’s Faculty of Law, which is based on the Gardens Point Campus. Here the investigation focused on the use of computer-based flexible learning practices, as distinct from the more text-based practices identified within the original two sites.

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A well-engineered scaffold for regenerative medicine, which is suitable to be translated from the bench to the bedside, combines inspired design, technical innovation and precise craftsmanship. Electrospinning and additive manufacturing are separate approaches to manufacturing scaffolds for a variety of tissue engineering applications. A need to accurately control the spatial distribution of pores within scaffolds has recently resulted in combining the two processing methods, to overcome shortfalls in each technology. This review describes where electrospinning and additive manufacturing are used together to generate new porous structures for biological applications.

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Context: The Ober and Thomas tests are subjective and involve a "negative" or "positive" assessment, making them difficult to apply within the paradigm of evidence-based medicine. No authors have combined the subjective clinical assessment with an objective measurement for these special tests. Objective: To compare the subjective assessment of iliotibial band and iliopsoas flexibility with the objective measurement of a digital inclinometer, to establish normative values, and to provide an evidence-based critical criterion for determining tissue tightness. Design: Cross-sectional study. Setting: Clinical research laboratory. Patients or Other Participants: Three hundred recreational athletes (125 men, 175 women; 250 in injured group, 50 in control group). Main Outcome Measure(s): Iliotibial band and iliopsoas muscle flexibility were determined subjectively using the modified Ober and Thomas tests, respectively. Using a digital inclinometer, we objectively measured limb position. lnterrater reliability for the subjective assessment was compared between 2 clinicians for a random sample of 100 injured participants, who were classified subjectively as either negative or positive for iliotibial band and iliopsoas tightness. Percentage of agreement indicated interrater reliability for the subjective assessment. Results: For iliotibial band flexibility, the average inclinometer angle was -24.59 degrees +/- 7.27 degrees. A total of 432 limbs were subjectively assessed as negative (-27.13 degrees +/- 5.53 degrees) and 168 as positive (-16.29 degrees +/- 6.87 degrees). For iliopsoas flexibility, the average inclinometer angle was -10.60 degrees +/- 9.61 degrees. A total of 392 limbs were subjectively assessed as negative (-15.51 degrees +/- 5.82 degrees) and 208 as positive (0.34 degrees +/- 7.00 degrees). The critical criteria for iliotibial band and iliopsoas flexibility were determined to be -23.16 degrees and -9.69 degrees, respectively. Between-clinicians agreement was very good, ranging from 95.0% to 97.6% for the Thomas and Ober tests, respectively. Conclusions: Subjective assessments and instrumented measurements were combined to establish normative values and critical criterions for tissue flexibility for the modified Ober and Thomas tests.

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Learning capability (LC) is a special dynamic capability that a firm purposefully builds to develop a cognitive focus, so as to enable the configuration and improvement of other capabilities (both dynamic and operational) to create and respond to market changes. Empirical evidence regarding the essential role of LC in leveraging operational manufacturing capabilities is, however, limited in the literature. This study takes a routine-based approach to understand capability, and focuses on demonstrating leveraging power of LC upon two essential operational capabilities within the manufacturing context, i.e., operational new product development capability (ONPDC), and operational supplier integration capability (OSIC). A mixed-methods research framework was used, which combines sources of evidence derived from a survey study and a multiple case study. This study identified high-level routines of LC that can be designed and controlled by managers and practitioners, to reconfigure underlying routines of ONPDC and OSIC to achieve superior performance in a turbulent environment. Hence, the study advances the notion of knowledge-based dynamic capabilities, such as LC, as routine bundles. It also provides an impetus for managing manufacturing operations from a capability-based perspective in the fast changing knowledge era.

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Deterministic computer simulation of physical experiments is now a common technique in science and engineering. Often, physical experiments are too time consuming, expensive or impossible to conduct. Complex computer models or codes, rather than physical experiments lead to the study of computer experiments, which are used to investigate many scientific phenomena. A computer experiment consists of a number of runs of the computer code with different input choices. The Design and Analysis of Computer Experiments is a rapidly growing technique in statistical experimental design. This paper aims to discuss some practical issues when designing a computer simulation and/or experiments for manufacturing systems. A case study approach is reviewed and presented.

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Lean strategies have been developed to eliminate or reduce manufacturing waste and thus improve operational efficiency in manufacturing processes. However, implementing lean strategies requires a large amount of resources and, in practice, manufacturers encounter difficulties in selecting appropriate lean strategies within their resource constraints. There is currently no systematic methodology available for selecting appropriate lean strategies within a manufacturer's resource constraints. In the lean transformation process, it is also critical to measure the current and desired leanness levels in order to clearly evaluate lean implementation efforts. Despite the fact that many lean strategies are utilized to reduce or eliminate manufacturing waste, little effort has been directed towards properly assessing the leanness of manufacturing organizations. In practice, a single or specific group of metrics (either qualitative or quantitative) will only partially measure the overall leanness. Existing leanness assessment methodologies do not offer a comprehensive evaluation method, integrating both quantitative and qualitative lean measures into a single quantitative value for measuring the overall leanness of an organization. This research aims to develop mathematical models and a systematic methodology for selecting appropriate lean strategies and evaluating the leanness levels in manufacturing organizations. Mathematical models were formulated and a methodology was developed for selecting appropriate lean strategies within manufacturers' limited amount of available resources to reduce their identified wastes. A leanness assessment model was developed by using the fuzzy concept to assess the leanness level and to recommend an optimum leanness value for a manufacturing organization. In the proposed leanness assessment model, both quantitative and qualitative input factors have been taken into account. Based on program developed in MATLAB and C#, a decision support tool (DST) was developed for decision makers to select lean strategies and evaluate the leanness value based on the proposed models and methodology hence sustain the lean implementation efforts. A case study was conducted to demonstrate the effectiveness of these proposed models and methodology. Case study results suggested that out of 10 wastes identified, the case organization (ABC Limited) is able to improve a maximum of six wastes from the selected workstation within their resource limitations. The selected wastes are: unnecessary motion, setup time, unnecessary transportation, inappropriate processing, work in process and raw material inventory and suggested lean strategies are: 5S, Just-In-Time, Kanban System, the Visual Management System (VMS), Cellular Manufacturing, Standard Work Process using method-time measurement (MTM), and Single Minute Exchange of Die (SMED). From the suggested lean strategies, the impact of 5S was demonstrated by measuring the leanness level of two different situations in ABC. After that, MTM was suggested as a standard work process for further improvement of the current leanness value. The initial status of the organization showed a leanness value of 0.12. By applying 5S, the leanness level significantly improved to reach 0.19 and the simulation of MTM as a standard work method shows the leanness value could be improved to 0.31. The optimum leanness value of ABC was calculated to be 0.64. These leanness values provided a quantitative indication of the impacts of improvement initiatives in terms of the overall leanness level to the case organization. Sensitivity analsysis and a t-test were also performed to validate the model proposed. This research advances the current knowledge base by developing mathematical models and methodologies to overcome lean strategy selection and leanness assessment problems. By selecting appropriate lean strategies, a manufacturer can better prioritize implementation efforts and resources to maximize the benefits of implementing lean strategies in their organization. The leanness index is used to evaluate an organization's current (before lean implementation) leanness state against the state after lean implementation and to establish benchmarking (the optimum leanness state). Hence, this research provides a continuous improvement tool for a lean manufacturing organization.

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This thesis explored how an Australian, family owned, manufacturing firm responded to a design led innovation approach as conducted by the action researcher. Specifically, it investigated the barriers and opportunities that arose within the firm when trying to affect change to drive innovation. In doing so, key opportunities were identified that could help the firm to integrate a design led approach and remain competitive within an increasingly accessible global marketplace.

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Increasing global competition, rapid technological changes, advances in manufacturing and information technology and discerning customers are forcing supply chains to adopt improvement practices that enable them to deliver high quality products at a lower cost and in a shorter period of time. A lean initiative is one of the most effective approaches toward achieving this goal. In the lean improvement process, it is critical to measure current and desired performance level in order to clearly evaluate the lean implementation efforts. Many attempts have tried to measure supply chain performance incorporating both quantitative and qualitative measures but failed to provide an effective method of measuring improvements in performances for dynamic lean supply chain situations. Therefore, the necessity of appropriate measurement of lean supply chain performance has become imperative. There are many lean tools available for supply chains; however, effectiveness of a lean tool depends on the type of the product and supply chain. One tool may be highly effective for a supply chain involved in high volume products but may not be effective for low volume products. There is currently no systematic methodology available for selecting appropriate lean strategies based on the type of supply chain and market strategy This thesis develops an effective method to measure the performance of supply chain consisting of both quantitative and qualitative metrics and investigates the effects of product types and lean tool selection on the supply chain performance Supply chain performance matrices and the effects of various lean tools over performance metrics mentioned in the SCOR framework have been investigated. A lean supply chain model based on the SCOR metric framework is then developed where non- lean and lean as well as quantitative and qualitative metrics are incorporated in appropriate metrics. The values of appropriate metrics are converted into triangular fuzzy numbers using similarity rules and heuristic methods. Data have been collected from an apparel manufacturing company for multiple supply chain products and then a fuzzy based method is applied to measure the performance improvements in supply chains. Using the fuzzy TOPSIS method, which chooses an optimum alternative to maximise similarities with positive ideal solutions and to minimise similarities with negative ideal solutions, the performances of lean and non- lean supply chain situations for three different apparel products have been evaluated. To address the research questions related to effective performance evaluation method and the effects of lean tools over different types of supply chains; a conceptual framework and two hypotheses are investigated. Empirical results show that implementation of lean tools have significant effects over performance improvements in terms of time, quality and flexibility. Fuzzy TOPSIS based method developed is able to integrate multiple supply chain matrices onto a single performance measure while lean supply chain model incorporates qualitative and quantitative metrics. It can therefore effectively measure the improvements for supply chain after implementing lean tools. It is demonstrated that product types involved in the supply chain and ability to select right lean tools have significant effect on lean supply chain performance. Future study can conduct multiple case studies in different contexts.

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This paper seeks to explain the lagging productivity in Singapore’s manufacturing noted in the statements of the Economic Strategies Committee Report 2010. Two methods are employed: the Malmquist productivity to measure total factor productivity (TFP) change and Simar and Wilson’s (2007) bootstrapped truncated regression approach which first derives bias-corrected efficiency estimates before being regressed against explanatory variables to help quantify sources of inefficiencies. The findings reveal that growth in total factor productivity was attributed to efficiency change with no technical progress. Sources of efficiency were attributed to quality of worker and flexible work arrangements while the use of foreign workers lowered efficiency.

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Today, the majority of semiconductor fabrication plants (fabs) conduct equipment preventive maintenance based on statistically-derived time- or wafer-count-based intervals. While these practices have had relative success in managing equipment availability and product yield, the cost, both in time and materials, remains high. Condition-based maintenance has been successfully adopted in several industries, where costs associated with equipment downtime range from potential loss of life to unacceptable affects to companies’ bottom lines. In this paper, we present a method for the monitoring of complex systems in the presence of multiple operating regimes. In addition, the new representation of degradation processes will be used to define an optimization procedure that facilitates concurrent maintenance and operational decision-making in a manufacturing system. This decision-making procedure metaheuristically maximizes a customizable cost function that reflects the benefits of production uptime, and the losses incurred due to deficient quality and downtime. The new degradation monitoring method is illustrated through the monitoring of a deposition tool operating over a prolonged period of time in a major fab, while the operational decision-making is demonstrated using simulated operation of a generic cluster tool.

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Aims To integrate existing theoretical perspectives on change management, subjective fit and occupational stress to better understand the effects of change on employee adjustment. Background Although subjective fit with organizational goals and objectives has been shown to have positive effects on employee adjustment, its role in the organizational change–occupational stress context is not understood. This represents a caveat in research when considering the notion that those who feel that they fit with the organization's goals may be better equipped to reconcile and deal with change. Design A cross-sectional survey of nurses from public and non-profit sector hospitals was conducted. Method Data were collected from 252 public and non-profit sector nurses via online surveys. Data were collected from June–October in 2010. Structural equation modelling was used to test the direct and indirect effects among the focal variables. Results The results showed that public and non-profit nurses experience flexibility-limiting and flexibility-promoting change initiatives and that these are differentially related to the perception of administrative stressors and adjustment with these relationships directly and indirectly influenced by perceptions of subjective fit. Flexibility-limiting change initiatives led to lower levels of subjective fit, higher levels of administrative stressors and less favourable adjustment. On the other hand, flexibility-promoting change practices led to higher levels of subjective fit, lower levels of administrative stressors and ultimately better adjustment. Conclusion The results further the theoretical understanding of the role of subjective fit in organizational change and occupational stress theories.

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Lean strategies have been developed to eliminate or reduce waste and thus improve operational efficiency in a manufacturing environment. However, in practice, manufacturers encounter difficulties to select appropriate lean strategies within their resource constraints and to quantitatively evaluate the perceived value of manufacturing waste reduction. This paper presents a methodology developed to quantitatively evaluate the contribution of lean strategies selected to reduce manufacturing wastes within the manufacturers’ resource (time) constraints. A mathematical model has been developed for evaluating the perceived value of lean strategies to manufacturing waste reduction and a step-by-step methodology is provided for selecting appropriate lean strategies to improve the manufacturing performance within their resource constraints. A computer program is developed in MATLAB for finding the optimum solution. With the help of a case study, the proposed methodology and developed model has been validated. A ‘lean strategy-wastes’ correlation matrix has been proposed to establish the relationship between the manufacturing wastes and lean strategies. Using the correlation matrix and applying the proposed methodology and developed mathematical model, authors came out with optimised perceived value of reduction of a manufacturer's wastes by implementing appropriate lean strategies within a manufacturer's resources constraints. Results also demonstrate that the perceived value of reduction of manufacturing wastes can significantly be changed based on policies and product strategy taken by a manufacturer. The proposed methodology can also be used in dynamic situations by changing the input in the programme developed in MATLAB. By identifying appropriate lean strategies for specific manufacturing wastes, a manufacturer can better prioritise implementation efforts and resources to maximise the success of implementing lean strategies in their organisation.

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Roofing tile manufacturing is a mass production process with high operational and inventory wastes and costs. Due to huge operational costs, excessive inventory and wastes, and quality problems, roofing tile manufacturers are trying to implement lean manufacturing practice in their operations in order to remain competitive in an ncreasingly competitive global market. The aim of this research is to evaluate the possibility of reducing the operational and inventory costs of the tile manufacturing process through waste minimization. This paper analyses the current waste situation in a tile manufacturing process and develops current and future value stream mapping for such a process with a view to implementing lean principles in manufacturing. The focus of the approach is on cost reduction by eliminating non-value-added activities.

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Purpose – The purpose of this paper is to develop an effective methodology for implementing lean manufacturing strategies and a leanness evaluation metric using continuous performance measurement (CPM). Design/methodology/approach – Based on five lean principles, a systematic lean implementation methodology for manufacturing organizations has been proposed. A simplified leanness evaluation metric consisting of both efficiency and effectiveness attributes of manufacturing performance has been developed for continuous evaluation of lean implementation. A case study to validate the proposed methodology has been conducted and proposed CPM metric has been used to assess the manufacturing leanness. Findings – Proposed methodology is able to systematically identify manufacturing wastes, select appropriate lean tools, identify relevant performance indicators, achieve significant performance improvement and establish lean culture in the organization. Continuous performance measurement matrices in terms of efficiency and effectiveness are proved to be appropriate methods for continuous evaluation of lean performance. Research limitations/implications – Effectiveness of the method developed has been demonstrated by applying it in a real life assembly process. However, more tests/applications will be necessary to generalize the findings. Practical implications – Results show that applying the methods developed, managers can successfully identify and remove manufacturing wastes from their production processes. By improving process efficiency, they can optimize their resource allocations. Manufacturers now have a validated step by step methodology for successfully implementing lean strategies. Originality/value – According to the authors’ best knowledge, this is the first known study that proposed a systematic lean implementation methodology based on lean principles and continuous improvement techniques. Evaluation of performance improvement by lean strategies is a critical issue. This study develops a simplified leanness evaluation metric considering both efficiency and effectiveness attributes and integrates it with the lean implementation methodology.