Geomagnetic field influences probabilistic abstract decision-making in humans

To resolve disputes or determine the order of things, people commonly use binary choices such as tossing a coin, even though it is obscure whether the empirical probability equals to the theoretical probability. The geomagnetic field (GMF) is broadly applied as a sensory cue for various movements in many organisms including humans, although our understanding is limited. Here we reveal a GMF-modulated probabilistic abstract decision-making in humans and the underlying mechanism, exploiting the zero-sum binary stone choice of Go game as a proof-of-principle. The large-scale data analyses of professional Go matches and in situ stone choice games showed that the empirical probabilities of the stone selections were remarkably different from the theoretical probability. In laboratory experiments, experimental probability in the decision-making was significantly influenced by GMF conditions and specific magnetic resonance frequency. Time series and stepwise systematic analyses pinpointed the intentionally uncontrollable decision-making as a primary modulating target. Notably, the continuum of GMF lines and anisotropic magnetic interplay between players were crucial to influence the magnetic field resonance-mediated abstract decision-making. Our findings provide unique insights into the impact of sensing GMF in decision-makings at tipping points and the quantum mechanical mechanism for manifesting the gap between theoretical and empirical probability in 3-dimensional living space.Comment: 32 pages, 5 figures, 4 supplementary figures, 2 supplementary tables, and separate 15 ancillary file

Digital twin testbed and practical applications in production logistics with real-time location data

Nowadays, digital twins exist everywhere in various fields. However, an analysis of existing applications in manufacturing and logistics revealed that many entirely apply the concept. To identify when a complete implementation of the concept is beneficial, we analyse the need and the implications within production logistics. This study also presents an architecture supporting integrating a digital twin into production logistics and a corresponding application scenario. Based on this, we have derived practical applications. Each application is applied to different situations, and actual benefits can overcome the limitations of the previous studies

Integrating Smart Production Logisticswith Network Diagrams: A Frameworkfor Data Visualization

This paper introduces a framework that integrates smart production logistics(SPL) with network diagrams. This integration enhances visibility in the materialand information flow within the manufacturing sector, thereby adding valuethrough data visualization. Drawing from a detailed case study in the automotiveindustry, we outline the essential components of network diagrams that are tailoredto depict spatial-temporal data linked with material handling processes in an SPLcontext. This integrated approach presents managers with a new tool for optimizingplanning and executing tasks related to the transport of materials and information.Furthermore, while the framework brings about significant technological progress,it also emphasizes the managerial implications of SPL data visualization. In particular,it highlights its potential to foster informed decision-making, resource optimization,and strategic forecasting. The paper also discusses prospective researchavenues, stressing the importance of dynamic diagrams that decode complex patternsfrom digital data and the incorporation of sustainability metrics in SPL assessments.QC 20240416Part of ISBN 978-1-64368-511-3</p

Towards automatic validation of operation times in manual processes: Two industrial cases

For manual operations in assembly or production logistics is valid time data a prerequisite for engineering applications as well as cost efficient utilization of resources by enabling accurate planning and control of the operations. Recent development in digital technologies can supporta shift to a real-time and automatic gathering and analysis of operation times for manual materials handling and assembly operations. Still, questions arise on the use of such technologies for the case of measuring operation times, while considering e.g. personal integrity, data quality,as well as alignment to operational KPIs and engineering applications. This paper introduces two manufacturing engineering cases at two companies with a basic digital infrastructure in place and where operational KPIs are used for performance measurement and improvement.The first case presents a company in the early stages of its digitalization journey where process mapping, modelling and simulations of a real production situation builds the base for further investments in real-time data gathering solutions. The second case presents a situation of anengineering laboratory exploring and developing solutions to be fit for further introduction to the real production sites. These two case examples illustrate two distinct ends of a digital maturity spectrum, each one with specific challenges in introducing systems for automatic validation of operation times in manual processes. The cases are discussed in relation to the three earlier posed questions and related to challenges concerning operational dimensions (e.g. efficiency, flexibility, data quality, continuous improvement), human aspects (e.g. integrity,safety), technology aspects (e.g. data security, interoperability) and cost aspects (e.g. investment cost, running cost)

Integrating Smart Production Logisticswith Network Diagrams: A Frameworkfor Data Visualization

This paper introduces a framework that integrates smart production logistics(SPL) with network diagrams. This integration enhances visibility in the materialand information flow within the manufacturing sector, thereby adding valuethrough data visualization. Drawing from a detailed case study in the automotiveindustry, we outline the essential components of network diagrams that are tailoredto depict spatial-temporal data linked with material handling processes in an SPLcontext. This integrated approach presents managers with a new tool for optimizingplanning and executing tasks related to the transport of materials and information.Furthermore, while the framework brings about significant technological progress,it also emphasizes the managerial implications of SPL data visualization. In particular,it highlights its potential to foster informed decision-making, resource optimization,and strategic forecasting. The paper also discusses prospective researchavenues, stressing the importance of dynamic diagrams that decode complex patternsfrom digital data and the incorporation of sustainability metrics in SPL assessments.QC 20240416Part of ISBN 978-1-64368-511-3</p

Production Logistics Visibility - Perspectives, Principles and Prospects

Globalisation, competitive markets and increasing sustainabilityrequirements are demanding companies to focus on visibility to improve theirsupply chains and ultimately their businesses. This paper aims to identifyperspectives, principles and prospects of production logistics visibility (PLV). Thestudy is based on a literature review of articles presenting definitions, developmenttrends and the future role of PLV. It is concluded that visibility is generally definedby availability, quality, accessibility and usefulness of information. PLV could referto the extent to which actors within the production systems have access to timelyand accurate information considered useful to their operations. According to thefindings, antecedents of PLV include digitalisation, IoT and connectivity. Thesesteps are required to turn data into meaningful information that can be used fordecision making in production and logistics setting to improve operational andbusiness performance. Furthermore, to fully benefit from PLV, there has to be anintegration of external and internal perspectives. Concluding, the paper definesfuture research efforts including four lines of exploration and development: (1)Intra-site visibility for material management including dynamic synchronisation,takt and resource planning. (2) Supply-oriented visibility for dynamic status andprediction of supply network status. These two initial lines of enquiry should includethe perspectives of stakeholders, parameter, enabling technologies and potentialimpact. (3) A synthesised framework for Production Logistics Visibility, relying onutilizing antecedents and enabling multi-criteria decision in production logisticsbased on visibility, where performance in terms of efficiency, sustainability andflexibility is ensured. (4) To specifically detail and exploit the potential inproduction logistics visibility in the aspect of environmental sustainability andclosed material and product loops QC 20210115LOVI

Production Logistics Visibility - Perspectives, Principles and Prospects

Globalisation, competitive markets and increasing sustainabilityrequirements are demanding companies to focus on visibility to improve theirsupply chains and ultimately their businesses. This paper aims to identifyperspectives, principles and prospects of production logistics visibility (PLV). Thestudy is based on a literature review of articles presenting definitions, developmenttrends and the future role of PLV. It is concluded that visibility is generally definedby availability, quality, accessibility and usefulness of information. PLV could referto the extent to which actors within the production systems have access to timelyand accurate information considered useful to their operations. According to thefindings, antecedents of PLV include digitalisation, IoT and connectivity. Thesesteps are required to turn data into meaningful information that can be used fordecision making in production and logistics setting to improve operational andbusiness performance. Furthermore, to fully benefit from PLV, there has to be anintegration of external and internal perspectives. Concluding, the paper definesfuture research efforts including four lines of exploration and development: (1)Intra-site visibility for material management including dynamic synchronisation,takt and resource planning. (2) Supply-oriented visibility for dynamic status andprediction of supply network status. These two initial lines of enquiry should includethe perspectives of stakeholders, parameter, enabling technologies and potentialimpact. (3) A synthesised framework for Production Logistics Visibility, relying onutilizing antecedents and enabling multi-criteria decision in production logisticsbased on visibility, where performance in terms of efficiency, sustainability andflexibility is ensured. (4) To specifically detail and exploit the potential inproduction logistics visibility in the aspect of environmental sustainability andclosed material and product loops QC 20210115LOVI

Implementing transmission of data for digital twins in human-centered cyber-physical systems

This study proposes a model describing the functions and procedures for configuring the transmission of data of Digital Twins (DT) in humancenteredCyber-Physical Systems (CPS). We draw data from two cases including aircraft manufacturing and production logistics and presenttwo contributions. First, we derive a procedure identifying the steps and resources of data processing for DT in human-centered CPS. Second,we propose a systematic procedure for configuring bi-directional data transmission depending on the desired system utilization. These resultscontribute to realizing data processing activities supporting the implementation of DTs for human-centered CPS in manufacturing.QC 20240115Explainable and Learning Production Logistics by Artificial Intelligence (EXPLAIN

Machine learning in smart production logistics : a review of technological capabilities

Recent publications underscore the critical implications of adapting to dynamic environments forenhancing the performance of material and information flows. This study presents a systematicreview of literature that explores the technological capabilities of smart production logistics (SPL)when applying machine learning (ML) to enhance logistics capabilities in dynamic environments.This study applies inductive theory building and extends existing knowledge about SPL in threeways. First, it describes the role of ML in advancing the logistics capabilities of SPL across variousdimensions, such as time, quality, sustainability, and cost. Second, this study demonstrates the applicationof the component technologies of ML (i.e. scanning, storing, interpreting, executing, andlearning) to attain superior performance in SPL. Third, it outlines how manufacturing companiescan cultivate the technological capabilities of SPL to effectively apply ML. In particular, the studyintroduces a comprehensive framework that establishes the technological foundations of SPL, thusfacilitating the successful integration of ML, and the improvement of logistics capabilities. Finally,the study outlines practical implications for managers and staff responsible for the planning andexecution of tasks, including the movement of materials and information in factories.QC 20240724</p