Today’s agile production systems face an ever-increasing complexity due to individualized mass production, a volatile customer demand and dynamic events which disrupt the baseline schedule. ...Robustness and optimality of the schedule affect the efficiency of the production systems, which in turn negatively affects resource consumption and waste generation. To achieve near-optimal performance, while adhering to due dates and robustly handling disturbances, predictive-reactive scheduling is often proposed. In the current state-of-the-art research on predictive-reactive scheduling there still exist some open issues. One issue to address is a current deficit in generalization, that is, when handling new, previously unseen data. Arguably the main culprit is the reactive (re)scheduling component. Designing such highly complex systems imposes many difficulties. We identify existing problems which ultimately limit the applicability of predictive-reactive scheduling and investigate and evaluate a design approach for predictive-reactive scheduling. We propose predictive-reactive scheduling, which uses match-up scheduling and promising decentralized multi-agent reinforcement learning, which allows for fast and flexible real-time decision-making. The aim of this study is to provide insights and improve the applicability of research on predictive-reactive scheduling.
Purpose - 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.Design methodology approach - 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.Findings - 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.Research limitations implications - 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.Practical implications - 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.Originality value - 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.
Purpose
This paper reviews the synergy of Industry 4.0 and additive manufacturing (AM) and discusses the integration of data-driven manufacturing systems and product service systems as a key ...component of the Industry 4.0 revolution. This paper aims to highlight the potential effects of Industry 4.0 on AM via tools such as digitalisation, data transfer, tagging technology, information in Industry 4.0 and intelligent features.
Design/methodology/approach
In successive phases of industrialisation, there has been a rise in the use of, and dependence on, data in manufacturing. In this review of Industry 4.0 and AM, the five pillars of success that could see the Internet of Things (IoT), artificial intelligence, robotics and materials science enabling new levels of interactivity and interdependence between suppliers, producers and users are discussed. The unique effects of AM capabilities, in particular mass customisation and light-weighting, combined with the integration of data and IoT in Industry 4.0, are studied for their potential to support higher efficiencies, greater utility and more ecologically friendly production. This research also illustrates how the digitalisation of manufacturing for Industry 4.0, through the use of IoT and AM, enables new business models and production practices.
Findings
The discussion illustrates the potential of combining IoT and AM to provide an escape from the constraints and limitations of conventional mass production whilst achieving economic and ecological savings. It should also be noted that this extends to the agile design and fabrication of increasingly complex parts enabled by simulations of complex production processes and operating systems. This paper also discusses the relationship between Industry 4.0 and AM with respect to improving the quality and robustness of product outcomes, based on real-time data/feedback.
Originality/value
This research shows how a combined approach to research into IoT and AM can create a step change in practice that alters the production and supply paradigm, potentially reducing the ecological impact of industrial systems and product life cycle. This paper demonstrates how the integration of Industry 4.0 and AM could reshape the future of manufacturing and discusses the challenges involved.
Agility drivers, enablers and outcomes Vázquez‐Bustelo, Daniel; Avella, Lucía; Fernández, Esteban
International journal of operations & production management,
01/2007, Volume:
27, Issue:
12
Journal Article
Peer reviewed
Purpose
Despite the fact that agile manufacturing has been frequently promoted as a means of improving business competitiveness, little empirical evidence exists in the literature validating its ...positive link with business performance. The purpose of this research paper is to analyse agile manufacturing in Spain and study whether it is a critical factor for success in different industries.
Design/methodology/approach
A conceptual model is drawn up, based on the literature and a previous case study, to relate turbulence in the environment with agile manufacturing practices and business performance. The model is tested on a large sample of Spanish manufacturers using a survey methodology to obtain information and a structural equation model to analyse the data.
Findings
The results obtained show that, in turbulent environments, the integrated use of agile manufacturing practices promotes manufacturing competitive strength, leading to better operational, market and financial performance.
Research limitations/implications
This study has two main limitations. First, it is difficult to determine the most suitable unit of analysis when studying agile manufacturing. Second, single respondent bias may be considered a limitation.
Practical implications
Managers should consider the integrated implementation of agile manufacturing practices in order to develop manufacturing strength and to outperform competitors in turbulent business environments.
Originality/value
This study adopts a systematic approach to the analysis of agile manufacturing, considering various agility practices or enablers in an integrated way and relating them not only to environmental characteristics but also to business performance. This approach is especially interesting because most of the literature on agile manufacturing deals with agility strategies or techniques in an isolated way. The study also tests the suitability of agile manufacturing in real organisations – for the first time in the Spanish context.
Production systems must be able to quickly adapt to changing requirements. Especially in the field of remanufacturing, the uncertainty in the state of the incoming products is very high. Several ...adaptation mechanisms can be applied leading to agile and changeable production systems. Among these, adapting the degree of automation with respect to changeover times and high investment costs is one of the most challenging mechanisms. However, not only long-term changes, but also short-term adaptations can lead to enormous potentials, e.g. when night shifts can be supported by robots and thus higher labor costs and unfavorable working conditions at night can be avoided. These changes in the degree of automation on an operational level are referred to as fluid automation, which will be defined in this paper. The mechanisms of fluid automation are presented together with a case study showing its application on a disassembly station for electrical drives.
Purpose
The purpose of this paper is to develop and empirically assess a comprehensive operations and supply chain management (SCM) model. The theorized model incorporates supply chain market ...orientation, Just-in-Time (JIT) and Total Quality Management (TQM) as antecedents and agile production (AP) and green SCM (GSCM) practices as consequences.
Design/methodology/approach
Data from a sample of 136 US manufacturing managers were collected via an on-line survey firm. A partial least squares structural equation modeling is used to assess the efficacy of the theorized model.
Findings
Generally, market orientation supports the implementation of JIT and TQM, JIT and TQM support implementation of SCM, SCM supports implementation of AP and green supply chain management practices (GSCMP) and AP and GSCMP positively impact organizational performance.
Research limitations/implications
The model tested reflects the synergy created though the implementation of management improvement programs that support the six strategic imperatives of customer focus, efficiency, effectiveness, integration with supply chain partners, responsiveness, and environmental sustainability and the effects of those programs on the marketing and financial performance of manufacturing organizations.
Practical implications
The theorized model and results provide practicing managers with a blueprint for the systematic implementation of the improvement programs.
Originality/value
A comprehensive operations and SCM model is proposed and empirically assessed. The results of this investigation support the proposition that market orientation, JIT, TQM, SCM, AP and GSCMPs combine to positively affect organizational performance. The central role of the SCM construct is emphasized.
Nowadays battery cells are produced in high volumes and with no customization for lower demand quantities. Since battery technology is still evolving rapidly and production systems are an expensive, ...long-term investment, there is a need for adaptability of the production system to changing markets and technologies. This paper presents an approach to evaluate different configurations of a highly flexible production system for battery cells in different scenarios with the help of a digital twin and the definition of optimal system configurations. This permits the definition of a change strategy on how to move from one configuration to another.
The purpose of this study is to empirically assess the combined impact that Blockchain technology (BC), the Industrial Internet of Things (IIoT) technologies, and agile production have on supply ...chain performance. This study is narrowly based on the analysis of data from 303 U.S. manufacturing managers. The proposed theoretical model is analyzed following a covariance-based structural equation modeling methodology (CB/SEM). This is the first study to empirically assess the combined impact of Blockchain technology, IIoT technologies, and agile production on supply chain performance. The results support the conclusion that Blockchain and IIoT technologies are complementary and yield greater agility. Managers are provided with evidence that combining Blockchain, IIoT technologies, and agile production will lead to greater improvements in supply chain performance than using these technologies stand-alone.
Against the background of growing environmental awareness and ambitious international efforts against global warming, sales in the electric mobility sector are expected to rise steadily in the coming ...years. However, volatile markets accompanied by shorter product life cycles and uncertainties regarding legal, political and technological developments make it still difficult to forecast accurate figures and requirements of components such as batteries or electric motors. Therefore, the investment in highly productive but non-versatile production lines must be seen as a risk. Instead, the tension between need and uncertainty causes a need for rapidly adaptable, profitable production systems with low investment risk. In literature, the term "agile production systems" is often used in this context. Based on an extensive literature review, this paper therefore presents the state of research and attempts to develop a general definition of agile production systems in the context of electric mobility. In particular, relationships to existing production concepts are considered. The practical implementation of agile production systems is described using two different case studies. On the one hand, agile battery cell production based on modular and fully enclosed robotic cells is presented. This approach, based on microenvironments with adjustable humidity, enables a highly automated pouch cell production that is flexible in terms of material, number of units and format. Furthermore, the case study of an agile electric motor production is presented. Process chains of rotor and stator production are analyzed and an approach to conceptualize an agile production system for electric motors is introduced.
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