Recent Developments in Quality Management in the Era of Digital Transformation – A Review

The purpose of the current exploratory research is to trace the growth and evolution of the Quality Management as a critical function in organizations and as a discipline of study in academia and research. The methodology adapted is to review some of the classical works and research in the area of Quality Management, which indicates direction of growth and evolution. There are several pioneers who have contributed richly for building and shaping the Quality Management principles, practices and methodologies over several decades. The current study involved the task of summarizing significant trends of Quality Management starting from the crafts man era and going up to the current trend of managing Quality as part of digital transformation. In the digital era there is an increased emphasis on automation of all the activities related to product and process quality management. The use of IoT based automation starting from data capturing, archiving and the point of self-diagnostic and autonomous way of managing quality issues is common place in today’s industries Quality 4.0 era. There are several challenges along the way for which quality professionals must be equipped in terms of knowledge, skills and attitude necessary for quality problem solving using modern techniques. This aspect is also researched in this study. Familiarity with technology platforms such as artificial intelligence, machine learning, image processing, sensors and actuators and such other emerging technologies must form the arsenal for analyzing data and data patterns in the face of data deluge. This requires several inter and multi-disciplinary knowledge exchange forums for grooming future quality professional. This article aims at tracing the metamorphosis of quality management with focus on people development and continuous process improvements in the manufacturing and allied sectors

Cybersecurity for Manufacturers: Securing the Digitized and Connected Factory

As manufacturing becomes increasingly digitized and data-driven, manufacturers will find themselves at serious risk. Although there has yet to be a major successful cyberattack on a U.S. manufacturing operation, threats continue to rise. The complexities of multi-organizational dependencies and data-management in modern supply chains mean that vulnerabilities are multiplying. There is widespread agreement among manufacturers, government agencies, cybersecurity firms, and leading academic computer science departments that U.S. industrial firms are doing too little to address these looming challenges. Unfortunately, manufacturers in general do not see themselves to be at particular risk. This lack of recognition of the threat may represent the greatest risk of cybersecurity failure for manufacturers. Public and private stakeholders must act before a significant attack on U.S. manufacturers provides a wake-up call. Cybersecurity for the manufacturing supply chain is a particularly serious need. Manufacturing supply chains are connected, integrated, and interdependent; security of the entire supply chain depends on security at the local factory level. Increasing digitization in manufacturing— especially with the rise of Digital Manufacturing, Smart Manufacturing, the Smart Factory, and Industry 4.0, combined with broader market trends such as the Internet of Things (IoT)— exponentially increases connectedness. At the same time, the diversity of manufacturers—from large, sophisticated corporations to small job shops—creates weakest-link vulnerabilities that can be addressed most effectively by public-private partnerships. Experts consulted in the development of this report called for more holistic thinking in industrial cybersecurity: improvements to technologies, management practices, workforce training, and learning processes that span units and supply chains. Solving the emerging security challenges will require commitment to continuous improvement, as well as investments in research and development (R&D) and threat-awareness initiatives. This holistic thinking should be applied across interoperating units and supply chains.National Science Foundation, Grant No. 1552534https://deepblue.lib.umich.edu/bitstream/2027.42/145442/1/MForesight_CybersecurityReport_Web.pd

Semantic discovery and reuse of business process patterns

Patterns currently play an important role in modern information systems (IS) development and their use has mainly been restricted to the design and implementation phases of the development lifecycle. Given the increasing significance of business modelling in IS development, patterns have the potential of providing a viable solution for promoting reusability of recurrent generalized models in the very early stages of development. As a statement of research-in-progress this paper focuses on business process patterns and proposes an initial methodological framework for the discovery and reuse of business process patterns within the IS development lifecycle. The framework borrows ideas from the domain engineering literature and proposes the use of semantics to drive both the discovery of patterns as well as their reuse

The Digitalisation of African Agriculture Report 2018-2019

An inclusive, digitally-enabled agricultural transformation could help achieve meaningful livelihood improvements for Africa’s smallholder farmers and pastoralists. It could drive greater engagement in agriculture from women and youth and create employment opportunities along the value chain. At CTA we staked a claim on this power of digitalisation to more systematically transform agriculture early on. Digitalisation, focusing on not individual ICTs but the application of these technologies to entire value chains, is a theme that cuts across all of our work. In youth entrepreneurship, we are fostering a new breed of young ICT ‘agripreneurs’. In climate-smart agriculture multiple projects provide information that can help towards building resilience for smallholder farmers. And in women empowerment we are supporting digital platforms to drive greater inclusion for women entrepreneurs in agricultural value chains

The importance of Industry 4.0 technologies when selecting an ERP system – An empirical study

The paper deals with the issue of the impact of the “Industry 4.0” concept on the process of selection of the enterprise resource planning (ERP) system. Firstly, review of the literature regarding the ERP system selection is presented, with the emphasis on the role of the new technologies in such selection. Secondly, the content of the term “Industry 4.0” is discussed, and put into context with the nature of ERP systems. The main part of the article then presents the results of the survey conducted among the medium and large industrial companies in the Czech Republic. Employees in the position of decision makers in the matter of selecting an ERP system were asked to participate. The survey used the form of questionnaire with close-ended questions with five-point scales, and investigated the attitude of the Czech manufacturing companies to the selected technologies of “Industry 4.0” and the importance of particular criteria for the selection of new ERP system. Investigated criteria were divided into 9 groups, where 5 of them were derived from previous research on the topic of ERP systems selections, and dealt with system price, portability, modularity, user experience and security. The remaining 4 groups were aimed at the selected technologies of “Industry 4.0” – big data, system integration, cloud computing and automatic identification and data capture. Kruskal-Wallis test and Neményi method of post-hoc analysis were used to compare the importance of particular criteria expressed by the respondents. The results show that although the companies are aware of the future challenges raised by the “Fourth Industrial Revolution,” in the selection of ERP systems they still emphasise mostly the previously used criteria such as price or modularity. As for the criteria connected to “Industry 4.0,” the ability of a system to deal with big data was assessed as the most important one

Securing IT/OT Links for Low Power IIoT Devices:Design considerations for industry 4.0

Manufacturing is facing a host of new security challenges due to the convergence of information technology (IT) and operational technology (OT) in the industry. This article addresses the challenges that arise due to the use of low power Industrial Internet of Things (IIoT) devices in modular manufacturing systems of Industry 4.0. First, we analyze security challenges concerning the manufacturing execution system (MES) and programmable logic controllers (PLC) in IIoT through a selective literature review. Second, we present an exploratory case study to determine a protocol for cryptographic key management and key exchange suitable for the Smart Production Lab of Aalborg University (a learning cyber-physical factory). Finally, we combine the findings of the case study with a quality function deployment (QFD) method to determine design requirements for Industry 4.0. We identify specific requirements from both the high-level domain of factory capabilities and the low-level domain of cryptography and translate requirements between these domains using a QFD analysis. The recommendations for designing a secure smart factory focus on how security can be implemented for low power and low-cost IIoT devices. Even though there have been a few studies on securing IT to OT data exchange, we conclude that the field is not yet in a state where it can be applied in practice with confidence

IoT-enabled planning, control, and execution in ETO manufacturing: dynamics, requirements, and system architecture: a case study of Brunvoll AS

Confidential until 18. May 202