Reliability assessment of manufacturing systems: A comprehensive overview, challenges and opportunities

Reliability assessment refers to the process of evaluating reliability of components or systems during their lifespan or prior to their implementation. In the manufacturing industry, the reliability of systems is directly linked to production efficiency, product quality, energy consumption, and other crucial performance indicators. Therefore, reliability plays a critical role in every aspect of manufacturing. In this review, we provide a comprehensive overview of the most significant advancements and trends in the assessment of manufacturing system reliability. For this, we also consider the three main facets of reliability analysis of cyber–physical systems, i.e., hardware, software, and human-related reliability. Beyond the overview of literature, we derive challenges and opportunities for reliability assessment of manufacturing systems based on the reviewed literature. Identified challenges encompass aspects like failure data availability and quality, fast-paced technological advancements, and the increasing complexity of manufacturing systems. In turn, the opportunities include the potential for integrating various assessment methods, and leveraging data to automate the assessment process and to increase accuracy of derived reliability models

A review of applications of fuzzy sets to safety and reliability engineering

Safety and reliability are rigorously assessed during the design of dependable systems. Probabilistic risk assessment (PRA) processes are comprehensive, structured and logical methods widely used for this purpose. PRA approaches include, but not limited to Fault Tree Analysis (FTA), Failure Mode and Effects Analysis (FMEA), and Event Tree Analysis (ETA). In conventional PRA, failure data about components is required for the purposes of quantitative analysis. In practice, it is not always possible to fully obtain this data due to unavailability of primary observations and consequent scarcity of statistical data about the failure of components. To handle such situations, fuzzy set theory has been successfully used in novel PRA approaches for safety and reliability evaluation under conditions of uncertainty. This paper presents a review of fuzzy set theory based methodologies applied to safety and reliability engineering, which include fuzzy FTA, fuzzy FMEA, fuzzy ETA, fuzzy Bayesian networks, fuzzy Markov chains, and fuzzy Petri nets. Firstly, we describe relevant fundamentals of fuzzy set theory and then we review applications of fuzzy set theory to system safety and reliability analysis. The review shows the context in which each technique may be more appropriate and highlights the overall potential usefulness of fuzzy set theory in addressing uncertainty in safety and reliability engineering

Reliability assessment for hybrid systems of advanced treatment units of industrial wastewater reuse using combined event tree and fuzzy fault tree analyses

Advanced treatment units (ATUs) are highly recommended for industrial wastewater reuse in the developing countries especially in arid and semi-arid areas. Reliability of a hybrid treatment system comprised of a number of individual ATUs remains blur due to lack of conceptual framework, collected data or experience in failure performance analsis of these treatment systems. This paper presents a new methodological framework for assessing reliability of hybrid system alternatives in industrial wastewater treatment by using combined event tree analysis (ETA) and fault tree analysis (FTA). The framework comprises three major steps: (1) identification of feasible alternatives; (2) reliability analysis assessment using combined FTA and ETA with fuzzy logic techniques to calculate first failure probability of individual ATUs and then reliability of each hybrid system alternative; (3) prioritisation of alternatives. Failure probability rate of events in FTA is determined by experts’ judgement. The suggested framework is demonstrated through its application to a real case study of wastewater treatment plants of industrial parks in Iran. The results show the highest failure probabilities are reverse osmosis unit with 30% and ozonation unit with 24%, while coagulation and flotation unit has the lowest failure probability of 5.4%. The most reliable alternative of hybrid system is comprised of sand filter + activated carbon + micro filter + ultra-filter + ion exchange with 74.82% reliability. Results in this study also show that selecting ATUs with higher removal efficiencies or rate of acceptable scenarios to form a hybrid ATU system cannot necessarily lead to a more reliable hybrid system without performing suggested FTA and ETA in this paper

Signal and data processing for machine olfaction and chemical sensing: A review

Signal and data processing are essential elements in electronic noses as well as in most chemical sensing instruments. The multivariate responses obtained by chemical sensor arrays require signal and data processing to carry out the fundamental tasks of odor identification (classification), concentration estimation (regression), and grouping of similar odors (clustering). In the last decade, important advances have shown that proper processing can improve the robustness of the instruments against diverse perturbations, namely, environmental variables, background changes, drift, etc. This article reviews the advances made in recent years in signal and data processing for machine olfaction and chemical sensing

Industrial Applications: New Solutions for the New Era

This book reprints articles from the Special Issue "Industrial Applications: New Solutions for the New Age" published online in the open-access journal Machines (ISSN 2075-1702). This book consists of twelve published articles. This special edition belongs to the "Mechatronic and Intelligent Machines" section

Simulation and Economic Analysis of Coal Based Thermal Power Plant: A Critical Literature Review

ABSTRACT: Coal based fired power plant is a very complex unit. Today's electric energy is playing an important role in the industria

Assessing Food Safety Risk in Global Supply Chain

Despite many attempts in the food safety risk assessment, there are a few studies and methods to cover the entire food supply chain. This study introduce a new model to perform the food risk assessment considering human factor along the entire food supply chain. The multi-discipline methodology of risk assessment tool, in combination of Key Performance Indicators (KPIs) has been applied in order to assess high safety risk point along the entire supply chain of food products. The method has been validated through the application in a case studies of food production

Business analytics in industry 4.0: a systematic review

Recently, the term “Industry 4.0” has emerged to characterize several Information Technology and Communication (ICT) adoptions in production processes (e.g., Internet-of-Things, implementation of digital production support information technologies). Business Analytics is often used within the Industry 4.0, thus incorporating its data intelligence (e.g., statistical analysis, predictive modelling, optimization) expert system component. In this paper, we perform a Systematic Literature Review (SLR) on the usage of Business Analytics within the Industry 4.0 concept, covering a selection of 169 papers obtained from six major scientific publication sources from 2010 to March 2020. The selected papers were first classified in three major types, namely, Practical Application, Reviews and Framework Proposal. Then, we analysed with more detail the practical application studies which were further divided into three main categories of the Gartner analytical maturity model, Descriptive Analytics, Predictive Analytics and Prescriptive Analytics. In particular, we characterized the distinct analytics studies in terms of the industry application and data context used, impact (in terms of their Technology Readiness Level) and selected data modelling method. Our SLR analysis provides a mapping of how data-based Industry 4.0 expert systems are currently used, disclosing also research gaps and future research opportunities.The work of P. Cortez was supported by FCT - Fundação para a Ciência e Tecnologia within the R&D Units Project Scope: UIDB/00319/2020. We would like to thank to the three anonymous reviewers for their helpful suggestions