The Effectiveness of Virtual R&D Teams in SMEs: Experiences of Malaysian SMEs

The number of small and medium enterprises (SMEs), especially those involved with research and development (R&D) programs and employed virtual teams to create the greatest competitive advantage from limited labor are increasing. Global and localized virtual R&D teams are believed to have a high potential for SMEs growth. Due to the fast growing complexity of the new product, coupled with new emerging opportunities of virtual teams, a collaborative approach is believed to be the future trend. This research explores the effectiveness of virtuality in SMEs virtual R&D teams. An online questionnaire emailed to Malaysian manufacturing SMEs and 74 usable questionnaires were received, representing a 20.8 percent return rate. To avoid the bias that may result from pre-suggested answer, a series of open-ended questions asked from expertise. This study based on analyzing an open-ended question; extract four main themes among expertise recommendations on the effectiveness of virtual teams for SMEs growth and performance. These are suitable for SMEs new product design manager to realize the key advantage and importance of virtual R&D teams in the process of NPD, which lead to increase the effectiveness of the new product's procedure.Virtual teams, New product development, Survey finding, Small and medium Enterprises.

Industry 4.0—from Smart Factory to Cognitive Cyberphysical Production System and Cloud Manufacturing

This book focuses on recent developments in new industrial platforms, with Industry 4.0 on its way to becoming Industry 5.0. The book covers smart decision support systems for green and sustainable machining, microscale machining, cyber-physical production networks, and the optimization of assembly lines. The modern multiobjective algorithms and multicriteria decision-making methods are applied to various real-world industrial problems. The emerging problem of cybersecurity in advanced technologies is addressed as well

Hybrid clouds and mass customization strategy a mid market utilization

Worldwide globalization processes as well as rapid development of information and communication technologies (ICT) significantly determine modern business operations in each and every organization. The basic concept of mass customization as a new trend is to increase the variety of individually tailored products/services to meet customer needs without a large increase in production costs. It requires a highly flexible production technology though. Developing such technologies can be expensive and time-consuming. Clouds enable delivery of mass customized services/information in the “Data to Information to Knowledge“ chain. The aim of this paper is to introduce the way how the mid-market can utilize Public Cloud computing in conjunction with a secure Private Clouds and further more to propose a framework for mass customization and its collaboration in Cloud

Industry 4.0 for SMEs

This open access book explores the concept of Industry 4.0, which presents a considerable challenge for the production and service sectors. While digitization initiatives are usually integrated into the central corporate strategy of larger companies, smaller firms often have problems putting Industry 4.0 paradigms into practice. Small and medium-sized enterprises (SMEs) possess neither the human nor financial resources to systematically investigate the potential and risks of introducing Industry 4.0. Addressing this obstacle, the international team of authors focuses on the development of smart manufacturing concepts, logistics solutions and managerial models specifically for SMEs. Aiming to provide methodological frameworks and pilot solutions for SMEs during their digital transformation, this innovative and timely book will be of great use to scholars researching technology management, digitization and small business, as well as practitioners within manufacturing companies

Industry 4.0 for SMEs

This open access book explores the concept of Industry 4.0, which presents a considerable challenge for the production and service sectors. While digitization initiatives are usually integrated into the central corporate strategy of larger companies, smaller firms often have problems putting Industry 4.0 paradigms into practice. Small and medium-sized enterprises (SMEs) possess neither the human nor financial resources to systematically investigate the potential and risks of introducing Industry 4.0. Addressing this obstacle, the international team of authors focuses on the development of smart manufacturing concepts, logistics solutions and managerial models specifically for SMEs. Aiming to provide methodological frameworks and pilot solutions for SMEs during their digital transformation, this innovative and timely book will be of great use to scholars researching technology management, digitization and small business, as well as practitioners within manufacturing companies

The functional fit between collaborative software and work systems:Qualification of work system needs to software functionality

The study develops an approach that tries to validate software functionality to work systems needs in SMEs. The formulated approach is constructed by using a SAAS based software i.e., work collaboration service (WCS), and SMEs as the elements of study. Where the WCS’s functionality is qualified to the collaboration needs that exist in operational and project work within SMEs. For this research constructivist approach and case study method is selected because the nature of the current study requires an in depth study of the work collaboration service as well as a detailed study of the work systems within different enterprises. Four different companies are selected in which fourteen interviews are conducted to gather data pertaining. The work systems method and framework are used as a central part of the approach to collect, analyze and interpret the enterprises work systems model and the underlying collaboration needs on operational and project work. On the other hand, the functional model of the WCS and its functionality is determined from functional model analysis, software testing, documentation and meetings with the service vendor. The enterprise work system model and the WCS model are compared to reveal how work progression differs between the two and make visible unaddressed stages of work progression. The WCS functionality is compared to work systems collaboration needs to ascertain if the service will suffice the needs of the project and operational work under study. The unaddressed needs provide opportunities to improve the functionality of the service for better conformity to the needs of enterprise and work. The results revealed that the functional models actually differed in how operational and project work progressed within the stages. WCS shared similar stages of work progression apart from the stages of identification and acceptance, and progress and completion stages were only partially addressed. Conclusion is that the identified unaddressed needs such as, single point of reference, SLA and OLA inclusion etc., should be implemented or improved within the WCS at appropriate stages of work to gain better compliance of the service to the needs of the enterprise an work itself. The developed approach can hence be used to carry out similar analysis for the conformance of pre-built software functionality to work system needs with SMEs

Big data reference architecture for industry 4.0: including economic and ethical Implications

El rápido progreso de la Industria 4.0 se consigue gracias a las innovaciones en varios campos, por ejemplo, la fabricación, el big data y la inteligencia artificial. La tesis explica la necesidad de una arquitectura del Big Data para implementar la Inteligencia Artificial en la Industria 4.0 y presenta una arquitectura cognitiva para la inteligencia artificial - CAAI - como posible solución, que se adapta especialmente a los retos de las pequeñas y medianas empresas. La tesis examina las implicaciones económicas y éticas de esas tecnologías y destaca tanto los beneficios como los retos para los países, las empresas y los trabajadores individuales. El "Cuestionario de la Industria 4.0 para las PYME" se realizó para averiguar los requisitos y necesidades de las pequeñas y medianas empresas. Así, la nueva arquitectura de la CAAI presenta un modelo de diseño de software y proporciona un conjunto de bloques de construcción de código abierto para apoyar a las empresas durante la implementación. Diferentes casos de uso demuestran la aplicabilidad de la arquitectura y la siguiente evaluación verifica la funcionalidad de la misma.The rapid progress in Industry 4.0 is achieved through innovations in several fields, e.g., manufacturing, big data, and artificial intelligence. The thesis motivates the need for a Big Data architecture to apply artificial intelligence in Industry 4.0 and presents a cognitive architecture for artificial intelligence – CAAI – as a possible solution, which is especially suited for the challenges of small and medium-sized enterprises. The work examines the economic and ethical implications of those technologies and highlights the benefits but also the challenges for countries, companies and individual workers. The "Industry 4.0 Questionnaire for SMEs" was conducted to gain insights into smaller and medium-sized companies’ requirements and needs. Thus, the new CAAI architecture presents a software design blueprint and provides a set of open-source building blocks to support companies during implementation. Different use cases demonstrate the applicability of the architecture and the following evaluation verifies the functionality of the architecture

The role of high-performance people management practices in Industry 4.0: The case of medium-sized Spanish firms

Purpose: This paper wants to build the case for the key role of high-performance people management practices in the development of I4.0 in SMEs. The research upon which this paper is based wants to prove that the consolidation of those practices should be a priority for any company willing to embark in this journey. The paper deals specifically with medium-sized Spanish firms which, on top, are already having significant issues with digitization. Design/methodology: The paper starts by digging into the literature to see how past technologies have impacted productivity, followed by a review of the material available on digitization and Industry 4.0. It moves on to explore the relationship between people management practices, productivity and innovation. Finally, the focus is placed on Spanish medium-sized companies, understanding their current levels of consolidation of high-performance people management practices as well as digitization. With all this information, several propositions are posited for validation using the Delphi methodology. Findings: I4.0 is, at its core, about productivity improvements through business process and business model innovation. People management practices are found to be strongly correlated with both productivity and innovation. It has also been found that Spanish medium-sized firms already have a significant initial gap compared to those of other OECD countries not only in productivity, but also people management practices and digitization. The experts seem to agree on the key role of people management practices and that they should be a high priority for any firm seriously thinking about industry 4.0. This is not to say that strategy or leadership will not play a paramount role in any digital transformation, but to emphasize the fact that the normally-forgotten people management practices will be important enablers in this process. Originality/value: It is believed that this is a topic that has been mostly neglected in the I4.0 literature. In that sense, the findings of this paper could be relevant for small and medium-sized businesses embarking on the industry 4.0 journey. This will entail a significant investment of time and money and, if the key role of people management practices is not on the radar screen, it may have significant implications for the success of those ventures.Peer ReviewedPostprint (published version

Cloud Manufacturing Model to Optimise Manufacturing Performance

Being predicted as the future of modern manufacturing, cloud-based manufacturing has drawn the attention of researchers in academia and industry. Researches are being done towards transforming every service in to cloud based service-oriented manufacturing mode in the manufacturing industry. There are many challenges that would arise when travelling towards this paradigm shift which is being addressed by researchers, but there are very few researches that concentrate on the elastic capability of cloud. Elastic capability makes this paradigm unique from all the other approaches or technologies. If elasticity is not achievable then the necessity of migrating to cloud is unnecessary. So, it is imperative to identify if at all it is necessary to adopt cloud-based manufacturing mode and discuss the issues and challenges that would arise to achieve elasticity when shifting to this emerging manufacturing paradigm. This research explores the importance of adopting cloud-based manufacturing mode to improve manufacturing performance based on the competitive priorities such as cost, quality, delivery and flexibility and proposes an elasticity assessment tool to be included in the cloud-based manufacturing model for the users to assess the challenges and issues on the realisation of elasticity on the context of manufacturing, which is the novelty of this research. The contribution to knowledge is a clear understanding of the necessity of cloud based elastic manufacturing model in the manufacturing environment for the manufacturing SMEs to gain a competitive advantage by achieving the competitive priorities such as low-cost, high-quality, and on-time delivery. Finally, the research suggests the best combination of manufacturing parameters that has to be emphasised to improve the manufacturing performance and gain a competitive advantage