Blockchain Enabled Quality Management in Short Food Supply Chains

© 2022 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0).Food system (re)localisation involves moving food systems back to local areas and a result are the short food supply chains. Food system (re)localisation is occurring to offset the perceived negative impacts of global food systems. Short food supply chains may face challenges in terms of quality set at national and international levels. Short food supply chains will benefit from technologies that can be developed to meet specific requirements which can be significantly different from those in conventional level food supply chains. One such digital technology is blockchain. This paper aims to present a blockchain based quality management architecture developed for short food supply chains. Requirements for the blockchain architecture are based on existing literature on quality management in food supply chains, with an emphasis on the specifics of quality and re-localisation in short food supply chains. Also considered in the architecture are the characteristic features of blockchain, with some emphasis on trust management and smart contracts. The adoption considerations regarding the resulting architecture are highlighted. It is concluded that the architecture has features relevant to the short food supply chain that differs from conventional food supply chains. Future work regarding implementation and validation of the architecture developed is suggested.Peer reviewedFinal Published versio

Intelligent decision support for maintenance: an overview and future trends

The changing nature of manufacturing, in recent years, is evident in industry’s willingness to adopt network-connected intelligent machines in their factory development plans. A number of joint corporate/government initiatives also describe and encourage the adoption of Artificial Intelligence (AI) in the operation and management of production lines. Machine learning will have a significant role to play in the delivery of automated and intelligently supported maintenance decision-making systems. While e-maintenance practice provides aframework for internet-connected operation of maintenance practice the advent of IoT has changed the scale of internetworking and new architectures and tools are needed. While advances in sensors and sensor fusion techniques have been significant in recent years, the possibilities brought by IoT create new challenges in the scale of data and its analysis. The development of audit trail style practice for the collection of data and the provision of acomprehensive framework for its processing, analysis and use should be avaluable contribution in addressing the new data analytics challenges for maintenance created by internet connected devices. This paper proposes that further research should be conducted into audit trail collection of maintenance data, allowing future systems to enable ‘Human in the loop’ interactions

EU H2020 MSCA RISE Project FIRST - “virtual Factories: Interoperation suppoRting buSiness innovation”

FIRST – “virtual Factories: Interoperation suppoRting buSiness innovation”, is a European H2020 project, founded by the RESEARCH AND INNOVATION STAFF EXCHANGE (RISE) Work Programme as part of the Marie Skłodowska-Curie actions. The project concerns with Manufacturing 2.0 and aims at providing the new technology and methodology to describe manufacturing assets; to compose and integrate the existing services into collaborative virtual manufacturing processes; and to deal with evolution of changes. This Chapter provides an overview of the state of the art for the research topics related to the project research objectives, and then it presents the progresses the project achieved up to now towards the implementation of the proposed innovations

Towards an understanding of business design within enterprise architecture management: a cautionary tale

Includes bibliographical references.Business Design represents a set of concepts that are described in the literature as providing a sound foundation for sustainable competitive advantage into the future. The particular values underpinning Business design are based on the enablement of a design thinking approach to solving the imponderable problems that organisations regularly encounter. In particular, the application of a design thinking approach to Business Design requires that resultant system designs are economically viable and technologically feasible. Enterprise Architecture Management plays a vital role in supporting these latter two requirements. Yet the definition of Enterprise Architecture Management as the 'normative restriction of design freedom' (Deitz, 2011) implies constraints that could impose limits on such business design. Consequently, the qualitative inductive research described in this document was undertaken to explore the perceived paradoxical relationship between Business Design and Enterprise Architecture Management. This dissertation recounts the process and results of this research initiative based on data recorded during interviews with a number of management level staff at a leading South African Insurance organisation. The participants were intimately involved in a programme to, amongst other objectives, establish a platform to support enterprise-wide Business Design within Enterprise Architecture Management, a programme that was experiencing a number of challenges and that was still underway at the time of completion of this research. Findings arising from this research were that the varying perceptions and levels of commitment of business and IT stakeholders associated with the programme and its requirements, contributed significantly to these challenges. In addition to providing a rich description of the case organisation's journey towards the establishment of a Business Design platform, a sensitising framework – 'The 6 Cs Framework in Support of the Successful Enablement of Business Design within Enterprise Architecture Management' – is proposed as a useful tool to assist organisations that might be considering a similar programme in the future

Business Intelligence within Large Companies - Challenges and Maturity

Purpose: The purpose of the thesis is to create a Business Intelligence maturity model based on eight examined operational BI propositions. Furthermore it is to explore the recognition level and business impact of these propositions. Methodology: The work process consisted of an initial explorative phase where a theoretical framework was created based on literature research. Founding on that the maturity model was developed, and then further tested in a survey. The survey also examined the recognition level of the propositions. To explore the business impact of the propositions three in depth interviews were held. Conclusion: The main conclusions in the project are that the eight examined propositions are common challenges among large Scandinavian companies. The developed maturity model covers these challenges and can be used by organizations to see where they are at in their maturity curve and what the next step in the maturity process is. The higher the BI maturity is, the less recognized the propositions are. The recognition level of propositions and the BI maturity impact the business success, and the BI maturity among large Scandinavian companies is somewhat moderate. Other conclusions are that a well functioning BI environment is essential for any large organization since it enables the achieving of strategic goals such as efficient and effective processes. However, efficientBI-­processes and a functioning IT landscape can be difficult to establish, especially for large companies. There are extensive amounts of data to process, the implementation costs are high, and the needed change management resources are often overlooked