The classical view of cyber-physical systems is that the integration computing, communication and control elements are considering only physical computational elements, neglecting human one.This paper presents a on an anthropocentric reference architecture for smart factories (ACPA4SF), where key characteristic its model relies unified integrality which can not be further decomposed into smaller engineering artefacts without loosing functionality.The describes some preliminary insides in...

To engineer the factory of future paper argues for an anthropocentric cyber-physical reference model that assimilate in integrated, dynamic, structural and functional way all required components (i.e. physical, computational human) a synthetic hybrid system. This is due to real need design large-scale complex systems accommodate latest achievements automation where human not merely playing simple clear role inside control-loop, but becoming composite factor highly automated system...

Industrial processes often rely on high-temperature heat, traditionally generated through the combustion of fossil fuels. However, a significant shift towards renewable and sustainable heat sources is underway, supported by environmental policies actions such as European Green Deal. These energy systems are complex characterized high degree interdependencies between various parameters. Optimizing orchestrating these for efficient delivery requires careful consideration factors temperature...

This article evaluates several machine learning methods to substitute the missing light detection and ranging data for better spatial localization of industrial automated guided vehicles. Decision trees ensemble using bagging or boosting techniques have been considered. Also, k-nearest neighbors algorithm was analyzed. Most algorithms evaluated based on multiple criteria hyper parameter tuning. The analysis results done in a comparative way, regression evaluation metrics being experiments...

Manufacturing companies, independent of operation sector and size, must be able to produce lot size one products, just-in-time at a competitive cost. Coping with this high adaptability short reaction times proves very challenging. New approaches taken into consideration for designing modular, intelligent cooperative production systems which are easy integrate the entire factory. The coined term network interacting artefacts system is cyber-physical (CPS). CPS often used in context Industry...

The paper investigates the cognitive complexity associated with design of group decision processes (GDP) in relation some basic contextual factors such us task complexity, users' creativity and problem space complexity.The analysis is done by conducting a socio-simulation experiment for an envisioned software tool that acts as collaborative environment GDP design.The simulation results provide insights on how to engineer context-adaptable functionalities aiming at minimizing design.Although...

In the modelling of Cyber-Physical Systems (CPSs), there are different possible routes that can be followed to gradually achieve a collection constituent models co-simulated with high level accuracy.This paper demonstrates methodology which initially develops all at abstraction discreteevent expressed using Vienna Development Method (VDM).Subsequently, number these refined (without changing interfaces) by more detailed in formalisms, and tools export Functional Mock-up Units (FMUs) for...

Industrial assistive systems result from a multidisciplinary effort that integrates IoT (and IoT), Cognetics, and Artificial Intelligence. This paper evaluates the Prediction by Partial Matching algorithm as component of an assembly assistance system supports factory workers, providing choices for next manufacturing step. The evaluation proposed method was performed on datasets collected within experiment involving trainees experienced workers. goal is to find out which best suits in order...

The paper highlights the computational power of swarming models (i.e., stigmergic mechanisms) to build collaborative support systems for complex cognitive tasks such as facilitation group decision processes (GDP) in e-meetings. Unlike traditional approaches that minimize complexity by incorporating knowledge into system, coordination mechanisms providing system with emergent functionalities are shaped environment itself through possibility structure it terms high-level artefacts. This is...

Abstract The spreadsheet applications are becoming a widely used tool for processing quantitative data and developing analytical solutions. ability to build decision support systems (DSS) based on these solutions can facilitate knowledge management increase information utilization within an organization. paper describes the use of solution partially implement performance-based budgeting (PB) principles public body. builds goal programming optimization method is exemplified some real data.

Autonomous mobile robots (AMRs) are gaining popularity in various applications such as logistics, manufacturing, and healthcare. One of the key challenges deploying AMR is estimating their travel time accurately, which crucial for efficient operation planning. In this article, we propose a novel approach using Long Short-Term Memory (LSTM) networks. Our involves training network synthetic data generated simulation environment digital twin AMR, virtual representation physical robot. The...

In this paper, we analyse Markov prediction as a suitable model to suggest the next assembly step in manufacturing process. The goal is decision support system which can assist workers factory, at least their training period, manually assemble product. We evaluate proposed context-based predictor on dataset collected through an experiment involving 68 trainees and compare it with our previously implemented two-level predictors. consisted of assembling tablet composed seven components. were...

This paper presents the design of a prediction-based assembly assistance system for manual operations and results obtained on data collected from experiments assembling customizable product. We integrated into proposed Markov predictor improved with padding mechanism whose role is to recommend next step detect worker's errors. The trained correct patterns tested real assembly/manufacturing data. improves coverage and, thus, there significantly higher number steps which are correctly...