A conceptual framework for linking worker and organizational needs to data and information requirements

Data and information intensiveness is increasing at the shop floor in the manufacturing industry, which leads to the fragmentation of tasks as the needed information is often scattered in different places. The challenge is to provide correct and right amount of information both to increase job satisfaction of workers and to increase productivity. The objective of this study is to identify what kind of manufacturing data, information and intelligent knowledge is needed by workers at the shop floor, and to identify the requirements when opening the knowledge flows between the shop floor and management processes. As a results of the study, a conceptual framework is created to link workers’ and organizational needs to data and information requirements. The framework identifies information and knowledge flows from and to required human-machine interfaces. This study also highlights the link between work processes at the shop floor to the innovation and organizational learning processes of manufacturing companies

Quantum computing challenges in the software industry. A fuzzy AHP-based approach

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Evaluating worker-centered smart interventions on the shop floor

This paper presents the evaluation strategy and the first results we obtained when we used the FACTS4WORKERS evaluation framework. The purpose of the framework is to prove whether the project interventions achieve the expected results, which are: improving workers’ job satisfaction, increasing innovation and problem solving skills as well as enhancing productivity. Because of the diversity of the industrial partners and of the workplaces where the interventions are going to be implemented, the different languages, legal and cultural environments the framework was conceived as general as possible to be adapted to any particular case. We present here one example for using the framework, the first results of these measurements and the feedback the evaluation provides both for supporting the decisions about the interventions and about the framework itself

Quantum computing challenges in the software industry. A fuzzy AHP-based approach

ContextThe current technology revolution has posed unexpected challenges for the software industry. In recent years, the field of quantum computing (QC) technologies has continued to grow in influence and maturity, and it is now poised to revolutionise software engineering. However, the evaluation and prioritisation of QC challenges in the software industry remain unexplored, relatively under-identified and fragmented.ObjectiveThe purpose of this study is to identify, examine and prioritise the most critical challenges in the software industry by implementing a fuzzy analytic hierarchy process (F-AHP).MethodFirst, to identify the key challenges, we conducted a systematic literature review by drawing data from the four relevant digital libraries and supplementing these efforts with a forward and backward snowballing search. Second, we followed the F-AHP approach to evaluate and rank the identified challenges, or barriers.ResultsThe results show that the key barriers to QC adoption are the lack of technical expertise, information accuracy and organisational interest in adopting the new process. Another critical barrier is the lack of standards of secure communication techniques for implementing QC.ConclusionBy applying F-AHP, we identified institutional barriers as the highest and organisational barriers as the second highest global weight ranked categories among the main QC challenges facing the software industry. We observed that the highest-ranked local barriers facing the software technology industry are the lack of resources for design and initiative while the lack of organisational interest in adopting the new process is the most significant organisational barrier. Our findings, which entail implications for both academicians and practitioners, reveal the emergent nature of QC research and the increasing need for interdisciplinary research to address the identified challenges.</p

Enhancing smartness and interoperability of building management systems in non-residential buildings

In smart and sustainable cities, smartness of buildings is expected to evolve. A smart building should enhance its users’ productivity and minimize its environmental impact. Although these objectives are seemingly common, the development of the smartness of buildings is actualized in the form of an incoherent combination of standards and solutions. The emergence of the IoT (Internet of Things) is expected to bring major improvements in the development of smartness, but at the same time, it may even worsen non-systematicity. Such inconsistency creates barriers to the commercialization of innovations and poses challenges to technical building management. Here, we clarify the situation between the conventional building management system approach and the IoT-based entrants. We analyze the different approaches to building automation systems’ interoperability by means of a literature review, professional interviews and smart readiness indicator impact evaluation. The study forms a general view based on the presented information and suggests approaches for specifying technical building systems, which are expected to improve their schematic clarity and reduce performance gaps of buildings. This study can be used as a practical tool by technical building managers, and it discusses issues needing consideration to the benefit of policymakers, industry and academia