Journal of Manufacturing Technology Management
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Increased digitalization has influenced various business activities including companies’ business models (BMs) by enabling various new forms of cooperation between companies and leading to new product and service offerings as well as new forms of company relationships with customers and employees. At the same time, this digitalization has put pressure on companies to reflect on their current strategy and explore new business opportunities systematically and at early stages. While research on digitalization in the context of BMs is now gaining increased attention, a research gap still exists in this field since the number of empirical insights is limited. The paper aims to discuss these issues.
Qualitative empirical data collected from 12 key informants working in two distinctive industries, the media and automotive industries, were collected. An investigation was carried out to examine the differences and similarities among how digitalization influences a company’s value creation, proposition and capture, as well as how firms cope with challenges presented by increased digitalization.
The findings of the study show that, whilst digitalization is generally considered to be important, the value proposition itself as also the position in the value network determine the perceived available options for business model innovation (BMI) by digitalization. Moreover, the organizational capacities and employee competences were identified as future challenges that will be faced by both industries.
The findings of this study have revealed that representatives of the media and automotive industries perceive both the pressures and opportunities of digitalization regarding BMI; its application and exploitation, however, remain challenging. This study contributes to the existing body of knowledge by providing empirical insights in the context of digitalization and BMI.
Manufacturing companies must have a good knowledge of their products and processes to be competitive. This is increasingly important as products become more complex. There are many recent developments in product representation, but these do not currently address manufacturing process issues, or integrate with techniques such as key characteristics and Variation Risk Management. This paper describes the development of a database which models complex product specifications, down to component feature detail. It allows the representation of manufacturing operations, process chains and costs, and maps these models. Key product characteristics are flowed down to the detailed feature level, and the associated variability and capability assessed. The paper commences by outlining some of the recent significant developments in product representation. The database structure and associated applications are described. Finally, an example is provided for the use of the database, based on the representation of gas turbine engine from a major aerospace manufacturing company.
The purpose of this paper is to propose a methodology to reduce the potential risk of failures in high‐volume manufacturing.
The research documented here represents an even balance of theoretical and practical development, with validation of the methodology – referred to as integrated risk minimisation (IRM).
The success of the IRM is measured in terms of reduced defect rates, through either prediction or earlier detection of defects. The combination of an inline design and immediate operator feedback on all detected defects was a critical design element.
The electroplating process was chosen as a suitable case study to provide the platform from which the IRM could be developed and tested. Implementation into industry has generated the proof to support the IRM as a methodology that can successfully reduce potential risks in high‐volume manufacturing.
In a unique approach, failure modes and effects analysis is built into the IRM methodology, thus establishing a “closed loop” process. The IRM methodology is suitably generic, to allow the achievement of similar results for any high‐volume process.
– There is significant evidence of increasing global implementation failures in enterprise resource planning (ERP) projects; and, for this reason, critical success factors (CSF) on implementation success (IS) are of notable concern to manufacturing organizations. This paper aims to focus on these factors and the role they played toward implementation success of ERP projects in India. Furthermore, this paper will also seek to explore whether the implementation success is moderated (i.e. influenced) by the organizational culture. This will help other manufacturing organizations take appropriate decisions about the ERP implementation.
– In the proposed model, the authors propose organizational culture as the moderator toward the implementation success of ERP projects in India. A survey methodology is used for the study, and a structured questionnaire was developed to get the information.
– Through this study, it has been found that the organizational culture acts as a moderator and moderates the relationship between CSF and implementation success of the ERP projects in India.
– This study offers both academicians and practitioners a model to research, assess, and identify the appropriate CSF such as Setting up ERP business goals and objectives (SEB), Cross-Functional Teams (CFT), Business Process Reengineering (BPR), Projects Tracking (PTG), and Data Analysis and Conversion (DAG) on IS of ERP projects in India and moderated by the organizational culture. The research is targeted on manufacturing organizations in India, and hence it has limitations in terms of scope. However, the results are quite encouraging with very good response (
– Unfortunately, few research studies define the issues related to the moderator namely the organizational culture. This paper demonstrates how this moderator played an important role in ERP implementation. The findings will encourage Indian manufacturing organizations to implement ERP when facing challenges of the competitive market for their competitive advantage. For India, this research could be among the first to its nature.
The “resource‐based view” (RBV) of firms considers that major operational and organisational advantages are created in the internal environment of a firm. The implementation of lean manufacturing represents the potential for strategic advantage over competitors, especially in craft‐based industries in developing regions of the world. The purpose of this paper is to investigate the relationship between the adoption of lean manufacturing and market share and value creation of companies in the agricultural machinery and implements sector in Brazil.
The paper is based on data collected in a survey conducted across 37 firms in the agricultural machinery and implements industry in Brazil. The data were used within a model for assessing the degree of leanness to test three hypotheses using correlation, regression, analysis of variance and cluster statistical methods.
Brazilian firms and managers in this sector that have supported a transition towards the adoption (and adaptation) of lean manufacturing practices have shown a significant improvement in their business performance.
The paper presents an empirical study where lean manufacturing is investigated and tested from a “RBV” perspective. It demonstrates the application of an emergent model for measuring the degree of leanness and the extent of business improvement. The study and the model are applied to smaller, craft‐based industries and so is applicable in developing countries and regions, in comparison with most literature on lean production in advanced economies. It provides a useful perspective for firms to corroborate and understand the potential benefits that lean manufacturing can bring if adopted.
Flexibility has become one of the most useful and necessary weapons in many of today's competitive markets. For companies in situations considering investments in flexibility, it is necessary to assess carefully exactly what flexibility could benefit the company's operations, and how this flexibility can be achieved. Different manufacturing situations are associated with different levels of uncertainty and variations, and therefore call for different sorts of flexibility. Although flexibility has been argued to be available (to a certain point) without major investments in technology, it can be assumed that flexibility is most likely to come at a price. A company should therefore spend considerable effort on identifying what flexibility would be of benefit to the organisation to enhance their performance, and thereafter assess how to achieve it. This paper provides a comprehensive analysis of variability and uncertainty, and therefore, the need for flexibility within an organisation by examining market and manufacturing process related factors. Each factor is further examined to find out relevant flexibilities and corresponding methods, tools, and techniques to be used by suggesting proposed manufacturing approaches to organisations. The human factor is suggested as an essential flexibility component as well as a key contributor for selecting, developing, improving and implementing flexibilities in order to succeed in markets that are accelerating and becoming more turbulent.
This paper aims to present a model of a multi‐phase multi‐product manufacturing system considering a CONstant work‐in‐process (CONWIP) control mechanism and using continuous‐time Markov chain modelling approach.
The model includes defining a state space then constructing the rate matrix, which contains the transition rates, followed by formulating the transition matrix. The time‐dependent probabilities that a product is in a particular state at a certain time are characterized. Performance measures related to the statistics on the waiting time and average number of work‐in‐process in the production system have been determined. Consequently, a numerical example is presented to illustrate the computations of different model aspects.
The analyses explain a foundation needed for analyzing the steady state behavior of manufacturing systems. Results have shown how production data can be easily modified for what‐if analyses by the use of Excel add‐in tool.
The multi‐level model outlines a framework that provides a practical tool for production engineers seeking to enhance the performance of their production system by selecting the best order release mechanism.
A novel aspect of the work reported in this paper is the application of Chapman‐Kolmogrov mathematics and CONWIP ordering theory, which is developed for evaluating and managing CONWIP controlled production systems.
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