Mass-customization production (MCP) companies must fight with shop-floor uncertainty and complexity caused by wide variety of product components. The research is motivated by a typical MCP company ...that has experienced inefficient scheduling due to paper-based identification and manual data collection. This paper presents an RFID-enabled real-time manufacturing execution system (RT-MES). RFID devices are deployed systematically on the shop-floor to track and trace manufacturing objects and collect real-time production data. Disturbances are identified and controlled within RT-MES. Planning and scheduling decisions are more practically and precisely made and executed. Online facilities are provided to visualize and manage real-time dynamics of shop-floor WIP (work-in-progress) items. A case study is reported in a collaborating company which manufactures large-scale and heavy-duty machineries. The efficiency and effectiveness of the proposed RT-MES are evaluated with real-life industrial data for shop-floor production management in terms of workers, machines and materials.
► RFID technology is deployed to MCP concerned manufacturing objects to capture real-time data. ► Disturbances are captured by RFID to form a real-time adaptive decision mode. ► Any movements of materials are captured by RFID and WIP inventory level is reduced finally.
Full text
Available for:
GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
To fill the reference model gaps in the Manufacturing Execution System (MES) platform software field, the definitions for platform software and reference model are put forward, and a reference model ...for MES platform conforming to Industrie 4.0 specification is proposed. The MES platform was characterized by the reference model from three dimensions of problem space, lifetime and infrastructure, in which, each dimension was represented by a view that consists of a number of viewpoints. In building the reference model, the viewpoints selection processes were discussed based on the current standards in each area corresponding to each dimension, and then a concept of reference model building block was defined. Furthermore, in order to explain how the reference model can be applied in use, some examples were performed for a representative application scenario in Industrie 4.0 and illustrating the reference model in combination with the application of specific technologies. A conclusion and expectation for the reference model research were summarized in the end of the paper.
Industry 4.0 dictates the end of traditional centralized applications for production control. Its vision of ecosystems of smart factories with intelligent and autonomous shop-floor entities is ...inherently decentralized. Responding to customer demands for tailored products, these plants fueled by technology enablers such as 3D printing, Internet of Things, Cloud computing, Mobile Devices and Big Data, among others create a totally new environment. The manufacturing systems of the future, including manufacturing execution systems (MES) will have to be built to support this paradigm shift.
This work makes a case for the integration of the increasingly popular and largely separate topics of Industry 4.0 and the circular economy (CE). The paper extends the state-of-the-art literature by ...proposing a pioneering roadmap to enhance the application of CE principles in organisations by means of Industry 4.0 approaches. Advanced and digital manufacturing technologies are able to unlock the circularity of resources within supply chains; however, the connection between CE and Industry 4.0 has not so far been explored. This article therefore contributes to the literature by unveiling how different Industry 4.0 technologies could underpin CE strategies, and to organisations by addressing those technologies as a basis for sustainable operations management decision-making. The main results of this work are: (a) a discussion on the mutually beneficial relationship between Industry 4.0 and the CE; (b) an in-depth understanding of the potential contributions of smart production technologies to the ReSOLVE model of CE business models; (c) a research agenda for future studies on the integration between Industry 4.0 and CE principles based on the most relevant management theories.
Academics and practitioners have long acknowledged the importance of agile manufacturing and related supply chains in achieving firm sustainable competitiveness. However, limited, if any, research ...has focused on the evolution of practices within agile manufacturing supply chains and how these are related to competitive performance objectives. To address this gap, we reviewed the literature on an agile manufacturing drawing on the evolution of manufacturing agility, attributes of agile manufacturing, the drivers of agile manufacturing, and the identification of the enabling competencies deployable for agile manufacturing. Our thesis is that agile manufacturing is at the centre of achieving a sustainable competitive advantage, especially in light of current unprecedented market instability coupled with complex customer requirements. In this regard, the emphasis which agile manufacturing places on responsive adaptability would counter the destabilising influence of competitive pressures on organisations performance criteria. We have identified five enabling competencies as the agility enablers and practices of agile manufacturing, that is, transparent customisation, agile supply chains, intelligent automation, total employee empowerment and technology integration, and further explored their joint deployment to create positive multiplier effects. Future research directions were also provided with respect to the operationalisation of the five identified enablers and the potential for emergent technologies of big data, blockchain, and Internet of Things to shape future agile manufacturing practices.
Full text
Available for:
BFBNIB, GIS, IJS, IZUM, KILJ, KISLJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Firms do not currently fully appreciate the complex characteristics of Industry 4.0 and as a result are uncertain about what it represents for them. In this study, an assessment model is developed to ...measure the level of implementation of Industry 4.0 technologies, around three dimensions: 'Factory of the Future', 'People and Culture', and 'Strategy'. The 'Factory of the Future' is the main dimension and is composed of eight attributes: Additive Manufacturing, Cloud, Manufacturing Execution System, Internet of Things and Cyber Physical Systems, Big Data, Sensors, e-Value Chains, and Autonomous Robots. The study uses a defence manufacturing firm to develop, test and validate the model and report on 12 partners. We concluded that the focal firm has an Industry 4.0 maturity level of 59.35, above the sector average of 55.58. This research contributes by empirically developing a model and providing an analysis of major firms in the Defence supply network.
Full text
Available for:
BFBNIB, GIS, IJS, KISLJ, NUK, PNG, UL, UM, UPUK
•Trends in Industry 4.0 (I4.0) are influencing the development of manufacturing execution systems.•I4.0-related requirements of MES functionalities are determined.•MESs should interconnect all ...components of cyber-physical systems.•Formal models and ontologies will play essential role in I4.0 systems.•The overview can serve as a guide for engineers as well as for researchers.
This work presents how recent trends in Industry 4.0 (I4.0) solutions are influencing the development of manufacturing execution systems (MESs) and analyzes what kinds of trends will determine the development of the next generation of these technologies. This systematic and thematic review provides a detailed analysis of I4.0-related requirements in terms of MES functionalities and an overview of MES development methods and standards because these three aspects are essential in developing MESs. The analysis highlights that MESs should interconnect all components of cyber-physical systems in a seamless, secure, and trustworthy manner to enable high-level automated smart solutions and that semantic metadata can provide contextual information to support interoperability and modular development. The observed trends show that formal models and ontologies will play an even more essential role in I4.0 systems as interoperability becomes more of a focus and that the new generation of linkable data sources should be based on semantically enriched information. The presented overview can serve as a guide for engineers interested in the development of MESs as well as for researchers interested in finding worthwhile areas of research.
Full text
Available for:
GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
The automated design of imaging systems involving no or minimal human effort has always been the expectation of scientists, researchers and optical engineers. In addition, it is challenging to choose ...an appropriate starting point for an optical system design. In this paper, we present a novel design framework based on a point-by-point design process that can automatically obtain high-performance freeform systems. This framework only requires a combination of planes as the input based on the configuration requirements or the prior knowledge of designers. This point-by-point design framework is different from the decades-long tradition of optimizing surface coefficients. Compared with the traditional design method, whereby the selection of the starting point and the optimization process are independent of each other and require extensive amount of human effort, there are no obvious differences between these two processes in our design framework, and the entire design process is mostly automated. This automated design process significantly reduces the amount of human effort required and does not rely on advanced design skills and experience. To demonstrate the feasibility of the proposed design framework, we successfully designed two high-performance systems as examples. This point-by-point design framework opens up new possibilities for automated optical design and can be used to develop automated optical design in the areas of remote sensing, telescopy, microscopy, spectroscopy, virtual reality and augmented reality.
Cognitive robots, able to adapt their actions based on sensory information and the management of uncertainty, have begun to find their way into manufacturing settings. However, the full potential of ...these robots has not been fully exploited, largely due to the lack of vertical integration with existing IT infrastructures, such as the manufacturing execution system (MES), as part of a large-scale cyber-physical entity. This paper reports on considerations and findings from the research project STAMINA that is developing such a cognitive cyber-physical system and applying it to a concrete and well-known use case from the automotive industry. Our approach allows manufacturing tasks to be performed without human intervention, even if the available description of the environment-the world model-suffers from large uncertainties. Thus, the robot becomes an integral part of the MES, resulting in a highly flexible overall system.
Cloud manufacturing (CM) and Internet of things (IoT) are interlinked, yet most works only focused on one of them and take the other as a constituent technology unit. This is practically inadequate, ...especially for a highly service-driven manufacturing execution system which entails systematical CM supports to respond to the real-time dynamics captured from the IoT-enabled execution hierarchy. To deal with the dynamics occurring in production logistics (PL) processes, this paper investigates a dynamic PL synchronization (PLS) of a manufacturer adopting public PL services. Contemporary CM and IoT infrastructures are systematically integrated to enable a smart PLS control mechanism with multi-level dynamic adaptability. The S-CM operation framework, operation logic, and PLS infrastructure are presented with an industrial case, and the effectiveness is also demonstrated and analyzed.
Full text
Available for:
DOBA, EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, IZUM, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, SIK, UILJ, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
PDF
