Classification Scheme for Root Cause and Failure Modes and Effects Analysis (FMEA) of Passenger Vehicle Recalls

Chi, Chia-Fen; Sigmund, Davin; Astardi, Martin Octavianus

doi:10.1016/j.ress.2020.106929

Cited by 37 publications

(15 citation statements)

References 21 publications

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“…Documented records of process and product control, personnel qualifications, workplace safety, and the environmental impact (reducing the consumption of raw materials and waste, reducing emissions, recycling, and the disposal methods used) are essential in this assessment during audits. In many industrial sectors (such as automotive, electromechanical, or chemical), suppliers are required to conduct risk analysis using FMEA (failure modes and effects analysis) for products and processes [17][18][19]. This analysis includes the determination of potential non-conformities, the probability of their occurrence, and the severity of possible errors for the company (occurrence of disruptions in processes, losses) and/or for customers.…”

Section: Introductionmentioning

confidence: 99%

Risk factors in the assessment of suppliers

et al. 2022

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The need to evaluate suppliers from the perspective of risk analysis by purchasing companies is increasing. Such evaluation of suppliers is conducted primarily by production companies with implemented quality (QMS), environmental (EMS), health and safety management systems (H&SMS), as well as Toyota Production System (TPS). This article aims to examine latent factors for suppliers’ evaluation and to describe the intensity of these factors by the implemented management system. The article provides the results of empirical research conducted with the computer-assisted telephone interviewing (CATI) technique in 151 medium and large manufacturing companies operating in Poland. The risk was classified into three main groups to deepen the research process: management system risks, environment risks, and process risks. This allowed for the formulation of some original conclusions. The results showed that companies implementing standardized management systems take the issue of risk analysis and management more seriously than organizations that do not implement such systems. The research also highlighted the differences in the perception of risk caused by implementing various management systems. The study also found that the industry and business profile specificity also affect the risk assessment in cooperation with suppliers.

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Section: Introductionmentioning

confidence: 99%

Risk factors in the assessment of suppliers

et al. 2022

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“…Moreover, such entities should provide the possibility of completing a transport operation with the lowest risk possible. The path to such a state of safety leads to the development and skilful application of risk management methods [ 18 , 19 , 20 ]. Unmanned aerial vehicles (UAVs), i.e., multirotors, planes, and helicopters, are devices that—due to their functional characteristics—are used on an increasingly wide scale in different areas of human activity.…”

Section: Introductionmentioning

confidence: 99%

Risk Management Model for Unmanned Aerial Vehicles during Flight Operations

Kobaszyńska-Twardowska

Łukasiewicz

Sielicki

2022

Materials

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Risk management and uncertainty models are practised in all branches of transport. Although unmanned aerial vehicles (UAVs) constitute a branch of the industry rather than transport as a whole, their development is oriented toward increasingly more serious applications involving the transport of goods and people. The constantly growing number of operations employing UAVs requires not only identification of hazard sources or risk assessment recommended by the applicable regulations, but also comprehensive risk management. In order to develop a systematic approach to risk management for air operations of UAVs, the classic risk management method can be used. This work proposes a novel multi-criteria risk model that may serve as the basis for further activities aimed at developing a risk management method for this domain. The model was based on six criteria and validated using a virtual route to risk assessment and valuation.

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“…Such a defect poses a significant risk of severe injury or death and may cause an unexpected and catastrophic failure of a component with little or no warning to the user. In [8], the authors surveyed various defects found in multiple automotive functional systems, such as electronics, steering systems, fuel systems, etc., on 345 passenger vehicles in the U.S.. According to the study, vital automotive components and systems accounted for half of all recalls.…”

Section: Introductionmentioning

confidence: 99%

Blockchain-Based Solution for Product Recall Management in the Automotive Supply Chain

Patro

Ahmad

Yaqoob³

et al. 2021

IEEE Access

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Product recall management in the automotive industry is a challenging problem that affects human lives and the safe operation of automobiles. Product recalls can assist in removing potentially unsafe products from the marketplace and minimizing a company's responsibility for corporate negligence. Today's systems and technologies leveraged for product recall management in the automotive supply chain fall short in providing transparency, traceability, reliability, audit, security, and trust features. In this paper, we propose a blockchain-based approach to overcome the aforementioned problems related to product recall management. We employ the public Ethereum blockchain and integrate it with the decentralized storage of the InterPlanetary File System (IPFS) to deal with the large-sized data problem. We present the system design and six algorithms explaining the working principles, information exchange flow, and stakeholders' detail and their sequential interactions. We discuss the implementation details, generalization aspects, and cost and security analyses to evaluate the performance of the proposed approach. The proposed solution is cost-effective, secure, and enables automakers to have end-to-end visibility of information during product recalls. We make the smart contracts' code publicly available on GitHub.

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Classification Scheme for Root Cause and Failure Modes and Effects Analysis (FMEA) of Passenger Vehicle Recalls

Cited by 37 publications

References 21 publications

Risk factors in the assessment of suppliers

Risk factors in the assessment of suppliers

Risk Management Model for Unmanned Aerial Vehicles during Flight Operations

Blockchain-Based Solution for Product Recall Management in the Automotive Supply Chain

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