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The purpose of this paper is to explore the relationship of strategic manufacturing effectiveness utilizing the four-stage model of Hayes and Wheelwright (H-W) with overall performance of manufacturing, market alignment and production competence (PC). In addition, it attempts to understand the relationship of strategic manufacturing effectiveness with manufacturing capability development modes, strategic groups of companies and the nature of improvement programs being employed.

Structured questionnaire was used to capture data from manufacturing organizations. Responses from managers of 47 Indian manufacturing companies were used to test the seven propositions that were developed to examine the paradigms of manufacturing competence.

The analysis revealed that the strategic manufacturing effectiveness of manufacturing companies based on H-W’s four-stage model has significant positive correlation with the overall performance of manufacturing and PC of the company. Further, the analysis substantiated the relationship of strategic manufacturing effectiveness with capability development process and the nature of improvement programs.

This exploratory study is based on a small sample of manufacturing companies with diversity and hence it may not be representative of all industry sectors. Second, it has used several scales for measuring the relevant constructs which themselves are not proven, hence, the findings should be taken with caution.

This is an initial research focussing on the relationships among different elements of manufacturing competence such as manufacturing capabilities, PC, manufacturing capability development mode and overall performance of manufacturing with strategic manufacturing effectiveness using H-W model. H-W model was primarily proposed as an audit tool for managers, was hitherto not adequately studied in relation to other paradigms of manufacturing competence.

Details the findings of a search for manufacturing “strategic groups” in the engineering industry, that is a set of firms competing within an industry on the basis of similar combinations of business scope and resource commitments. The research methodology used was to adopt stockturns (excluding work in process), as a measure of manufacturing scope. Manufacturing throughput efficiency was selected as a measure of production engineering resource commitment. An initial grouping of companies was accomplished by using these two manufacturing performance variables. Comparisons were then made of the manufacturing practices and performances of the firms in the four strategic groups that were formed. The results show statistically significant differences in the performance of each of the strategic groups formed. They can also serve as benchmarks for the evaluation of manufacturing management performance. The proposed manufacturing strategy and performance matrix provides a practical framework for strategic planning.

Globalization and the importance of emerging markets have increased the pressure of high-cost manufacturing locations to sustain operations. However, there are still some countries in which manufacturing is prospering despite high costs (like Germany, Sweden and Switzerland). This study examines seven competitive priorities through 24 different capabilities, using a case survey of four manufacturing companies located in Sweden. This study aims to develop a contemporary understanding from vital priorities and capabilities.

A case survey was conducted in four different-sized manufacturing companies in Sweden during the autumn of 2018. In total, the survey attracted 89 responses. Respondents were mainly middle managers and other management team members.

In general, companies assess the importance of manufacturing capabilities higher than performance and improvement. The authors’ analysis shows that quality priority through product and process capabilities is ranked highest in terms of importance, performance and improvement. In addition, delivery capability shows a similarity with quality. At the other end, being lowest ranked are typically different flexibility and advertising capabilities. This study demonstrates with correlation analysis that most often capabilities have a positive correlation in terms of their importance, performance and improvement needs. Some capabilities show potential correlations across importance, performance and improvement.

This research is limited to one high-cost environment and to four companies within that environment. Further research should examine the impact of the pandemic era on manufacturing priorities and capabilities.

In general, case surveys have relatively rarely been used in management studies. This research offers an alternative and deeper perspective from high-cost country manufacturing, as the responses are from numerous persons in management positions.

Total productive maintenance and total quality management are two lean manufacturing initiatives that are used by manufacturing plant managers to improve operations capabilities. The purpose of this paper is to investigate the effects of standalone lean practices and lean bundles on manufacturing business performance.

A quantitative approach was used. The survey data were drawn from 160 manufacturing organizations in India. The respondent companies were grouped on the basis of the duration of lean production in operation and then classified based on the profile of their operations strategy. The approach, based on comparative assessment between standalone lean practices and lean bundles, has been directed toward justification of lean bundles for its support to competitive manufacturing in the context of the Indian manufacturing sector.

The paper establishes the long-term effects of lean bundles in significantly improving manufacturing business performance as compared to standalone lean practices. Further findings of the study revealed the significance of the duration of lean production in operation in achieving higher levels of manufacturing business performance.

The study is cross-sectional in nature. It would be interesting to test the analytical framework adopted for this study for more industries and in different countries. The use of subjective measures in survey questionnaire is also another limitation of the study.

This study offers clear implications for practitioners, proving that they should give higher emphasis on the implementation of lean bundles using total productive maintenance and total quality management practices together, to prioritize their product, production and business strategies, to achieve sustainable competitive advantage.

This paper empirically examines and evaluates the effect of lean practices and bundles in the context of medium- and large-sized manufacturing industries in India. Besides, there are very few studies that comparatively assess the differences in performance contribution of various lean operational strategies considering duration of implementation of lean. Also, the theoretical contribution of the study establishes the essence of integrating total productive management and total quality management for attaining world class manufacturing is of high value.

The study re-examines if lean production manufacturing practices (i.e. TQM and JIT) interact with the compensation system (incentive vs. fixed compensation plans) and information system (i.e. attention directing goals and performance feedback) to reduce production costs (in terms of manufacturing and warranty costs) using a recursive partitioning model. Decision trees (i.e. recursive partitioning algorithm using Chi-square Automatic Interaction Detection or CHAID) are constructed on data from 77 U.S. manufacturing firms in the electronics industry. Overall, the “decision tree” results show significant interaction effects. In particular, the study found that better manufacturing performance (i.e. lower production costs) can be achieved when lean production manufacturing practices such as TQM and JIT are used along with incentive compensation plans. Also, synergies do result from combining TQM/JIT with more frequent performance feedback along with attention directing goals. These findings suggest that if organisational infrastructure and management control systems are not aligned with manufacturing practices, then the potential benefits of lean manufacturing (i.e. TQM and JIT) may not be fully realised.

As an advanced manufacturing method, additive manufacturing (AM) technology provides new possibilities for efficient production and design of parts. However, with the continuous expansion of the application of AM materials, subtractive processing has become one of the necessary steps to improve the accuracy and performance of parts. In this paper, the processing process of AM materials is discussed in depth, and the surface integrity problem caused by it is discussed.

Firstly, we listed and analyzed the characterization parameters of metal surface integrity and its influence on the performance of parts and then introduced the application of integrated processing of metal adding and subtracting materials and the influence of different processing forms on the surface integrity of parts. The surface of the trial-cut material is detected and analyzed, and the surface of the integrated processing of adding and subtracting materials is compared with that of the pure processing of reducing materials, so that the corresponding conclusions are obtained.

In this process, we also found some surface integrity problems, such as knife marks, residual stress and thermal effects. These problems may have a potential negative impact on the performance of the final parts. In processing, we can try to use other integrated processing technologies of adding and subtracting materials, try to combine various integrated processing technologies of adding and subtracting materials, or consider exploring more efficient AM technology to improve processing efficiency. We can also consider adopting production process optimization measures to reduce the processing cost of adding and subtracting materials.

With the gradual improvement of the requirements for the surface quality of parts in the production process and the in-depth implementation of sustainable manufacturing, the demand for integrated processing of metal addition and subtraction materials is likely to continue to grow in the future. By deeply understanding and studying the problems of material reduction and surface integrity of AM materials, we can better meet the challenges in the manufacturing process and improve the quality and performance of parts. This research is very important for promoting the development of manufacturing technology and achieving success in practical application.

Effective operations management systems (OMS) measurement remains a critical issue for theorists and practising managers (Neely, 2005; Bititci et al., 2012). Traditional labor efficiency measures sufficed when all that was made could be sold or when mass production systems filled warehouses with stock and the OMS had little relationship with “the consumer.” Modern manufacturing systems require a different form of flow optimization (beyond labor efficiency) measurement (Schmenner, 2015). The essential unit of measure for all OMS designs is the optimal use of time for process value adding and the flow of materials into and from the conversion process. Timely flow, therefore, satisfies the needs of multiple organizational stakeholders including cash flow (accounting), consumer reaction times (marketing) and the general steady state flow of materials (sales and supply chain). The purpose of this paper is to present the results of testing a new performance measure of operations flow effectiveness (OFE) with ten purposively selected cases.

The paper is theory building using ten, purposively selected, longitudinal case studies drawn from the UK high-value manufacturing (HVM) sector using a pluralist methodology of interviews, observation and secondary data.

The OFE measure provides a holistic view of material flow through the input-process-output cycles of a firm. The measure highlights OMS design weaknesses and flow inhibitors that reduce cash flow using a time-based approach to measuring OMS performance. The study validates the OFE measure and has identified six key design elements that enable high flow performance.

The paper tests a new process-focused flow performance measure. The measure supports a holistic approach to the manufacturing enterprise and allows different OMS designs to be evaluated so that organizational learning may be enacted to support performance improvement.

This study aims to examine the relationship between green technology implementation (GTI), knowledge management (KM) process and knowledge workers' operational performance (KWOP). The research postulates that a specific combination of GTI and KM processes can lead to improving KWOP.

The sample data (304) were taken from those manufacturing firms that are utilizing green technology. The examination was conducted by Smart PLS-SEM and fuzzy set qualitative comparative analysis (fsQCA). The Smart PLS 3.29 is used to verify certain variable relationships. Moreover, fsQCA is used to investigate multiple configuration paths to enhance KWOP.

The study's outcome indicated that GTI positively influences the KM process in manufacturing firms, and the KM process enormously improves KWOP. The fsQCA analysis result explores various integrations (communication, collaboration, supporting role and improved performance) with the KM (acquisition, sharing and utilization) process identified to enhance the performance of KWOP. The current study supports two merging methods to deepen understanding of employee operational performance.

The study methodologically contributes by integrating direct and configuration approaches to develop firms' operational performance. This study contributes to bridging research gaps in the prior literature and advances insight into the association between GTI, KM process and KWOP.

Examines the thirteenth published year of the ITCRR. Runs the whole gamut of textile innovation, research and testing, some of which investigates hitherto untouched aspects. Subjects discussed include cotton fabric processing, asbestos substitutes, textile adjuncts to cardiovascular surgery, wet textile processes, hand evaluation, nanotechnology, thermoplastic composites, robotic ironing, protective clothing (agricultural and industrial), ecological aspects of fibre properties – to name but a few! There would appear to be no limit to the future potential for textile applications.

This study aims to empirically investigate the impact of operational risk (i.e. supply, manufacturing and demand risks) on supply chain performance and the moderating role of integration (i.e. supplier, internal and customer integrations) in mitigating the impact of these risks, respectively.

A research framework of hypotheses is tested by structural equation modeling with data collected from the fourth round of the high-performance manufacturing project.

It is revealed that manufacturing and demand risks negatively impact operational performance, and more importantly, internal and customer integrations help to reduce the impact of these two risks. Additionally, the effects of both supply risk and supplier integration are only significant for large firms.

Supply chain managers need to appropriately develop the levels of integration to mitigate the adverse impact of operational risk.

Operational performance is always threatened by different types of risk that adversely affect the supply, production and demand sides of manufacturing firms. Despite this fact, large-scale data-based empirical research on the impact of operational risk on the performance of supply chains has been scarce. This study aims to fill this literature gap.