Digitally enhanced quality management for Zero-Defect Manufacturing

Though the idea of Zero Defect Manufacturing is not new, it remains a disruptive concept that is able to entirely reshape the manufacturing ideology. Existing literature suggests that Zero Defect Manufacturing can be implemented in two different approaches – namely product- (defective parts) and / or process-oriented (defective equipment) approaches. The recent onset of Industry 4.0 presents organizations with a plethora of technologies that promise to further enhance the quality of both products and processes, but also adds a third dimension to Zero Defect Manufacturing - people. Therefore, in this paper, we add the people-oriented approach as a third dimension to Zero Defect Manufacturing and draw on practical insights to present a framework for digitally enhanced quality management.publishedVersio

A global survey on the current state of practice in Zero Defect Manufacturing and its impact on production performance

To be competitive in dynamic and global markets, manufacturing companies are continuously seeking to apply innovative production strategies and methods combined with advanced digital technologies to improve their flexibility, productivity, quality, environmental impact, and cost performance. Zero Defect Manufacturing is a disruptive concept providing production strategies and methods with underlying advanced digital technologies to fill the gap. While scientific knowledge within this area has increased exponentially, the current practices and impact of Zero Defect Manufacturing on companies over time are still unknown. Therefore, this survey aims to map the current state of practice in Zero Defect Manufacturing and identify its impact on production performance. The results show that although Zero Defect Manufacturing strategies and methods are widely applied and can have a strong positive impact on production performance, this has not always been the case. The findings also indicate that digital technologies are increasingly used, however, the potential of artificial intelligence and extended reality is still less exploited. We contribute to theory by detailing the research needs of Zero Defect Manufacturing from the practitioner’s perspective and suggesting actions to enhance Zero Defect Manufacturing strategies and methods. Further, we provide practical and managerial suggestions to improve production performances and move towards sustainable development and zero waste.publishedVersio

Using the Process Digital Twin as a tool for companies to evaluate the Return on Investment of manufacturing automation

The fourth industrial revolution is gaining momentum, but still lacks full realization. Several studies suggest that many companies around the world have begun the digital transformation undertaking, but most are still far from full adoption and yet fail to see the full economic potential, being stuck in what has been called "pilot purgatory”. Digitalization is largely recognized as an accelerator and enabler for full automation in manufacturing, but companies are still struggling to assess the return on investment and the impact on operational performance indicators. Therefore, companies, especially SMEs characterized by dynamic, high-value, high-mix, and low-volume contexts, are reluctant to invest further. By incorporating simulation, data analytics and behavioral models, digital twins may also be used to support automation solutions ramp-up, demonstrate their impact evaluation, usage scenarios, eliminating the need for physical prototypes, reducing development time, and improving quality. Few forward-thinking companies are pursuing the digital transformation path, while the majority are clipping the wings of a transformation that is essential for a sustainable manufacturing. This paper describes a theoretical approach to exploit the digital twin technology to gather insights towards a realistic economical assessment of full automation solutions, to back and encourage investments to realize the potential of the digital manufacturing transformation. The approach is being tested under the European Union’s Horizon 2020 research and innovation program under grant agreement No. 958363, which provides an opportunity to assess how the various components of the method are constructed, how complex they are, and what level of effort is required, using a practical example.publishedVersio

A Cross-disciplinary, cross-organizational approach to sustainable design and product innovation in the aluminum industry

Aluminum is a promising sustainable and industrial resource that provides strong, lightweight structures with complex geometric possibilities, a high recovery rate in the recycling process, and low-emission production when produced by hydropower. Design and product innovations are enabling aluminum to increasingly replace steel in many industrial sectors (such as construction, automotive, and furniture), improving environmental (e.g., reduction of CO2 emission in transport) and financial (e.g., increased circularity and value creation) performance. However, key knowledge of the aluminum value chain is concentrated among the different actors. For instance, downstream actors possess a high level of technical expertise in the metallurgical properties and processing of aluminum, and they are typically situated a long distance from the end market or end user are unaware of the end user’s current and future needs. Investments in and investigations of new aluminum alloys, treatments, and machines are accompanied by high financial and time risks. Cross-disciplinary, cross-organizational collaborations might facilitate design and product innovations, including value creation and sustainability aspects and reducing financial and time risks. There is limited literature on how the different actors in the aluminum value chain should collaborate and which methods they should apply to increase sustainable design and product innovation. Therefore, this study applies a multiple case research approach to identify the benefits, enablers, and barriers of sustainable design and product innovation. Based on the findings, a sustainable design and product innovation framework was developed, highlighting actors, collaboration, and methods applied at different innovation project stages. The introduced approach supports the actors in the aluminum value chain to efficiently introduce sustainable design and product innovations to new and existing markets.publishedVersio

RINVE Feasibility Study 2018

This report summarizes end user needs and supplier capabilities within the "Automation and Robotics for Inspection and Maintenance" (RINVE) Network as identified in an innovation workshop held on the 10th of April 2018 at Gardermoen and a follow-up survey that was completed by the supplier companies in the network. The end user sectors considered in this report include: - Bridge inspection and maintenance - Railroad inspection and maintenance - Airport inspection and maintenance - Offshore inspection and maintenance The main purpose of the report is to serve as inspiration for new commercialization, research and development initiatives in Norway tied to the use of automation and robotics for inspection and maintenance work.publishedVersio

Enablers and inhibitors of Industry 4.0: results from a survey of industrial companies in Norway

Since 2011 when it was announced, Industry 4.0 has inspired a series of governmental and private programs worldwide. Nevertheless, it is an emerging research field and the academia calls for further explorative research, including on the enablers and inhibitors of Industry 4.0 implementation at national level. This paper addresses this topic based on a cross-sectional analysis of data collected through a two-step survey of 49 companies in Norway, 13 suppliers to the Oil and Gas industry and 36 from different manufacturing industries. The findings contribute primarily to the Training and Continuing Professional Development priority area in Kagermann et al. (2013)

Digitally enhanced quality management for Zero-Defect Manufacturing

Though the idea of Zero Defect Manufacturing is not new, it remains a disruptive concept that is able to entirely reshape the manufacturing ideology. Existing literature suggests that Zero Defect Manufacturing can be implemented in two different approaches – namely product- (defective parts) and / or process-oriented (defective equipment) approaches. The recent onset of Industry 4.0 presents organizations with a plethora of technologies that promise to further enhance the quality of both products and processes, but also adds a third dimension to Zero Defect Manufacturing - people. Therefore, in this paper, we add the people-oriented approach as a third dimension to Zero Defect Manufacturing and draw on practical insights to present a framework for digitally enhanced quality management

Reliability-based Cyber Plant

With the onset of Industry 4.0 several technological possibilities are offered in industry such as big data analytics, digital twin and augmented reality. The result is a more digitalised industry where faster and better decisions are possible. In long term this should provide a more reliable production with increased plant capacity and reduced downtime. To succeed with these possibilities a Cyber Physical Systems (CPS) must be established for the company. Currently, an own framework for CPS is under development and is expected to be tailored for Norwegian manufacturing. When building on the principle in Industry 4.0, big data capability with machine learning will be a fundamental model. Nevertheless, Industry 4.0 should also include other models for big data capability such as reliability modelling. The aim in this article is to present the current status of CPS framework and how it could be implemented in manufacturing industries. In particular, the article discusses and demonstrates the balance between machine learning and reliability engineering in big data analytics

Smart Maintenance in Asset Management – Application with Deep Learning

With the onset the digitalization and Industry 4.0, the maintenance function and asset management in a company is forming towards Smart Maintenance. An essential application in smart maintenance is to improve the maintenance planning function with better criticality assessment. With the aid from artificial intelligence it is considered that maintenance planning will provide better and faster decision making in maintenance management. The aim of this article is to develop smart maintenance planning based on principles both from asset management and machine learning. The result demonstrates a use case of criticality assessment for maintenance planning and comprise computation of anomaly degree (AD) as well as calculation of profit loss indicator (PLI). The risk matrix in the criticality assessment is then constructed by both AD and PLI and will then aid the maintenance planner in better and faster decision making. It is concluded that more industrial use cases should be conducted representing different industry branches

The Early Warning Procedure in an International Context

AbstractThe globalized business and organizational environment is creating a growing need for project managers that can operate in a variety of cultural and socio-economic settings and are capable of handling the complexities that arise while working in an international context. It is of course a very important aspect to be considered by project managers to identify the early warning signs of problems timely enough to take preventive actions in order to avoid undesired consequences. This act can be more challenging when performed in an international context which in nature is more complex. In this study we endeavour to scrutinize the early warning identification process as part of the management system in international projects and the possible obstacles which exist within this procedure. A real ongoing international R&D project will be used as an example to help us better clarifies the concept