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The purpose of this paper is to explore links between the process of strategy formulation and subsequent performance in operations within firms.

An in‐depth literature review on resource‐based and operations strategy naturally led to three hypotheses. These are then tested using evidence from field‐based case studies of manufacturing/assembly plants in the computer industry.

The research suggests that world‐class plants incorporate both strategic operations content and strategic operations processes, whilst low‐performing plants do not.

It is argued that involving manufacturing/operations managers in the strategic planning process helps align manufacturing and business strategy, and this alignment is associated with higher manufacturing performance. This should be of interest to operations managers and strategists within firms.

By linking strategic alignment and the manufacturing strategy process to world‐class manufacturing practices and performance, this research adds a new dimension to the study of world‐class manufacturing and more generally to the best practices and practice‐performance debates.

Hayes and Wheelwright, in postulating a more proactive strategic role of manufacturing, provided a four‐stage framework for the evaluation of manufacturing effectiveness. Reports on some results of an empirical study on the assessment of manufacturing effectiveness based on the Hayes‐Wheelwright (H‐W) framework. Highlights the operationalization of the H‐W framework as a strategic manufacturing audit tool and applies this tool to the manufacturing operations within a specific industry, namely the electronics industry. Aggregates and reports the results of the strategic manufacturing audits. In this way, provides an industry‐wide summary average of the strategic thinking and practices of manufacturing operations. This can then be used as the industry benchmark against which specific operations may be compared. Adds to the empirical database of manufacturing strategy and strategic manufacturing effectiveness as reported in the open literature. Provides a pragmatic strategic manufacturing audit tool that is based on the previously reported works of Hayes and Wheelwright.

Flexible Assembly Systems (FASs) are normally associated with the automatic, or robotic, assembly of products, supported by automated material handling systems. However, manual assembly operations are still prevalent within many industries, where the complexity and variety of products prohibit the development of suitable automated assembly equipment. This article presents a generic model for incorporating flexibility into the design and control of assembly operations concerned with high variety/low volume manufacture, drawing on the principles for Flexible Manufacturing Systems (FMS) and Just‐in‐Time (JIT) delivery. It is based on work being undertaken in an electronics company where the assembly operations have been overhauled and restructured in response to a need for greater flexibility, shorter cycle times and reduced inventory levels. The principles employed are in themselves not original. However, the way they have been combined and tailored has created a total manufacturing control system which represents a new concept for responding to demands placed on market driven firms operating in an uncertain environment.

The purpose of this paper is to develop an intelligent manufacturing system for transforming production management and operations to an Industry 4.0 manufacturing paradigm.

A manufacturing mode-Graduation Manufacturing System is designed for organizing and controlling production operations. An Industrial Internet of Things (IIoT) and digital twin-enabled Graduation Intelligent Manufacturing System (GiMS) with real-time task allocation and execution mechanisms is proposed to achieve real-time information sharing and production planning, scheduling, execution and control with reduced complexity and uncertainty.

The implementation of GiMS in an industrial company illustrates the potential advantages for real-time production planning, scheduling, execution and control with reduced complexity and uncertainty. For production managers and onsite operators, effective tools, such as cloud services integrates effective production and operations management strategies are needed to facilitate their decision-making and daily operations at the operational level.

This paper presents an Industry 4.0 paradigm-GiMS, which aims to explore Industry 4.0 technologies opportunities on operations and production management, especially on production planning, scheduling, execution and control.

Today′s changing global business environment requires firms to develop a better approach to global manufacturing operations. Of particular importance is the interaction between logistics and manufacturing activities. A survey of 101 senior manufacturing and materials managers revealed both important insight into the global co‐production decision and interesting comparative data for key value‐added activities. This research also evaluated the rationale behind, and overall benefit of, global manufacturing strategies. Presents key findings.

Lean and agile manufacturing are two initiatives that are used by manufacturing plant managers to improve operations capabilities. The purpose of this paper is to investigate internal and external factors that drive the choice of lean and agile operations capabilities and their respective impact on operational performance.

Lean and agile manufacturing are each conceptualized as a second‐order factor and measured through a bundle of distinct practices. The competitive intensity of industry and the competitive strategy are modeled as potential external and internal drivers, respectively, and the impact on quality, delivery, cost, and flexibility performance is analyzed using structural equations modeling. The model is tested with data from the high performance manufacturing project comprising a total of 211 plants from three industries and seven countries.

The results indicate that lean and agile manufacturing differ in terms of drivers and outcomes. The choice of a cost‐leadership strategy fully mediates the impact of the competitive intensity of industry as a driver of lean manufacturing, while agile manufacturing is directly affected by both internal and external drivers, i.e. a differentiation strategy as well as the competitive intensity of industry. Agile manufacturing is found to be negatively associated with a cost‐leadership strategy, emphasizing the difference between lean and agile manufacturing. The major differences in performance outcomes are related to cost and flexibility, such that lean manufacturing has a significant impact on cost performance (whereas agile manufacturing has not), and that agile manufacturing has a stronger relationship with volume as well as product mix flexibility than does lean manufacturing.

Cross‐sectional data from three industries and seven countries are used, and it would be interesting to test this model for more industries and countries.

The results provide insights into the factors that influence the choice of lean or agile manufacturing for improving operations, and the results that can be obtained.

To the authors' knowledge, this is the first large‐scale empirical survey of leanness and agility simultaneously, using data from manufacturing firms in Europe, Asia, and North America. The model incorporates a wide perspective on factors related to lean and agile manufacturing, to be able to identify similarities and differences.

The study presents various barriers to adopt big data analytics (BDA) for sustainable manufacturing operations (SMOs) post-coronavirus disease (COVID-19) pandemics. In this study, 17 barriers are identified through extensive literature review and experts’ opinions for investing in BDA implementation. A questionnaire-based survey is conducted to collect responses from experts. The identified barriers are grouped into three categories with the help of factor analysis. These are organizational barriers, data management barriers and human barriers. For the quantification of barriers, the graph theory matrix approach (GTMA) is applied.

The study presents various barriers to adopt BDA for the SMOs post-COVID-19 pandemic. In this study, 17 barriers are identified through extensive literature review and experts’ opinions for investing in BDA implementation. A questionnaire-based survey is conducted to collect responses from experts. The identified barriers are grouped into three categories with the help of factor analysis. These are organizational barriers, data management barriers and human barriers. For the quantification of barriers, the GTMA is applied.

The study identifies barriers to investment in BDA implementation. It categorizes the barriers based on factor analysis and computes the intensity for each category of a barrier for BDA investment for SMOs. It is observed that the organizational barriers have the highest intensity whereas the human barriers have the smallest intensity.

This study may help organizations to take strategic decisions for investing in BDA applications for achieving one of the sustainable development goals. Organizations should prioritize their efforts first to counter the barriers under the category of organizational barriers followed by barriers in data management and human barriers.

The novelty of this paper is that barriers to BDA investment for SMOs in the context of Indian manufacturing organizations have been analyzed. The findings of the study will assist the professionals and practitioners in formulating policies based on the actual nature and intensity of the barriers.

Introducing additive manufacturing (AM) in a multinational corporation with a global spare parts operation requires tools for a dynamic supplier selection, considering both cost and delivery performance. In the switchover to AM from conventional manufacturing, the objective of this study is to find situations and ways to improve the spare parts service to end customers.

In this explorative study, the authors develop a procedure – in collaboration with the spare parts operations managers of a case company – for dynamic operational decision-making for the selection of spare parts supply from multiple suppliers. The authors' design proposition is based on a field experiment for the procurement and delivery of 36 problematic spare parts.

The practice intervention verified the intended outcomes of increased cost and delivery performance, yielding improved customer service through a switchover to AM according to situational context. The successful operational integration of dynamic additive and static conventional supply was triggered by the generative mechanisms of highly interactive model-based supplier relationships and insignificant transaction costs.

The dynamic decision-making proposal extends the product-specific make-to-order practice to the general-purpose build-to-model that selects the mode of supply and supplier for individual spare parts at an operational level through model-based interactions with AM suppliers. The successful outcome of the experiment prompted the case company to begin the introduction of AM into the company's spare parts supply chain.

This paper aims to present a framework that will help manufacturing firms to configure their internal production and support operations to enable effective and efficient delivery of products and their closely associated services.

First, the key definitions and literature sources directly associated with servitization of manufacturing are established. Then, a theoretical framework that categorises the key characteristics of a manufacturer's operations strategy is developed and this is populated using both evidence from the extant literature and empirical data.

The framework captures a set of operations principles, structures and processes that can guide a manufacturer in the delivery of product‐centric servitized offering. These are illustrated and contrasted against operations that deliver purely product (production operations) and those which deliver purely services (services operations).

The work is based on a review of the literature supported by data collected from an exploratory case study. Whilst it provides an essential platform, further research will be needed to validate the framework.

The principal contribution of this paper is a framework that captures the key characteristics of operations for product‐centric servitized manufacture.

Presents a new design methodology and an integrated approach for the design of manufacturing systems. The methodology discusses the steps leading to design of manufacturing systems; the integrated approach suggests ways of integrating the different stages of manufacturing system design using genetic algorithms. The methodology and approach has been used for an industrial case study and the result has shown that the approach is effective.