Closed Loop Feedback Mechanism Effect Pilot Investigation on Manual Assembly Time and Process Variation

Krugh, Matthew; Garimella, Ravi Shankar; Baburaj, Adithya; Wescoat, Ethan; Mears, Laine

doi:10.1016/j.promfg.2020.05.025

Cited by 3 publications

(3 citation statements)

References 31 publications

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“…Gender [28], age [28], lack of experience [29], lack of knowledge [30][31][32][33][34], fatigue [25], stress [2], body physique [35], poor health [36], poor memory [36], personal life problems [36], personality type [25], disappointment [25], lack of motivation [25], depression [25], fear of failure [37], poor error visual error perception [25], financial problems [25,38], haste in doing work [39], low intelligence coefficient [25,38], job dissatisfaction [39], lack of trust in performance [25], misunderstanding [39], unintentional unsafe acts [39], sleep deprivation/disorder [6,27,40], risk-taking [41], and understanding roles and responsibilities [25,38].…”

Section: Individual Factorsmentioning

confidence: 99%

“…Based on some previous studies [29], the experience factor is an important factor affecting human errors in assembly systems. Some studies, such as [30][31][32][33][34], demonstrated that the lack of experience and knowledge of the assembler were the most effective personal factors that led to assembly errors. In addition, some studies demonstrated many personal factors, such as misunderstanding [39], visual error perception [25,38,84], risk-taking [41], worker memory [35,36,39], fatigue [6,25,[85][86][87], stress [2], understanding roles and responsibilities [25,38], unintentional unsafe acts and haste in doing work [39], worker health [36], and intelligence coefficient [25,38], were the root causes of human errors in manual assembly processes.…”

Section: Ranking Factors Influencing Hes Based On the Fuzzy Delphi Me...mentioning

confidence: 99%

See 1 more Smart Citation

A New Model for Determining Factors Affecting Human Errors in Manual Assembly Processes Using Fuzzy Delphi and DEMATEL Methods

Alqahtani,

Noman,

Alabdulkarim

et al. 2023

Symmetry

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Human errors (HEs) are common problems in manual assembly processes, impacting product quality and resulting in additional costs. Based on expert judgments, this study aims to identify the most significant factors affecting HEs in manual assembly processes and explore the cause-and-effect relationships among those factors. In order to achieve this objective, a proposed model is constructed using two types of Multi-Criteria Decision-Making (MCDM) techniques. Firstly, using two rounds of the fuzzy Delphi method (FDM), twenty-seven factors with an influence score of 0.7 or higher were found to have a major impact on HEs during manual assembly processes, with at least a 75% consensus among experts. After that, the twenty-seven factors affecting HEs were given to experts in a third round to analyze the cause-and-effect relationships among those factors using the fuzzy decision-making trial and evaluation laboratory (DEMATEL) method. In MCDM techniques, symmetry refers to an important property that can be used to find relationships between variables. It is based on the principle that the relative importance or preference between two variables should remain the same regardless of their positions or roles. Therefore, symmetry is a factor that MCDM approaches take into account to ensure that the relationships between variables are accurately represented, leading to more reliable decision-making outcomes. The reliability and normality of the surveying data were examined using the SPSS 22.0 software program. The study results revealed that training level, poor workplace layout, a lack of necessary tools, and experience were the major factors affecting HEs as root causes. Moreover, a failure to address the error-causing problem, unintentional unsafe acts, fatigue, and poor error visual perception were found to be effect (dependent) factors. The findings of this study can help organizations make better-informed decisions on how to reduce worker errors and interest in the factors that contribute to assembly errors and provide a good basis for reaching the quality of final assembled parts.

show abstract

Section: Individual Factorsmentioning

confidence: 99%

Section: Ranking Factors Influencing Hes Based On the Fuzzy Delphi Me...mentioning

confidence: 99%

A New Model for Determining Factors Affecting Human Errors in Manual Assembly Processes Using Fuzzy Delphi and DEMATEL Methods

Alqahtani,

Noman,

Alabdulkarim

et al. 2023

Symmetry

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show abstract

“…Effect feedback evaluation mechanism A follow-up survey is conducted in the cultivation of new entrepreneurial talents, and the feedback is collected. The measures to evaluate the entrepreneurial ability in the cultivation of entrepreneurial talents are put forward, which is helpful to improving the training mechanism of new entrepreneurial talents (Krugh et al, 2020).…”

Section: Entrepreneurial Practice Platformsmentioning

confidence: 99%

Innovative Strategies of Training Mechanism of Higher Education for New Entrepreneurial Talents

Wei

2021

Front. Psychol.

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With the development of the social economy, more and more talents are required in economic construction and innovation. The study aims to cultivate new entrepreneurial talents and promote the overall development of new ventures. First, the entrepreneurial ability of new entrepreneurial talents is analyzed, and the feasibility of improving the entrepreneurial ability of new entrepreneurial talents is verified. Second, the architecture is designed for improving the entrepreneurial ability of new entrepreneurial talents. About 350 employees in 20 ventures in Xi'an, Shaanxi Province are randomly selected as the subjects for a questionnaire survey (QS). Three-fifty questionnaires are distributed and 300 are collected. Descriptive statistics are used to analyze the 300 valid questionnaires. Then, the relationship between the psychological states of new entrepreneurial talents and their entrepreneurial ability is explored, and the influencing factors in the development of new entrepreneurial talents are analyzed. The results show that the number of employees in most ventures is between 250 and 400 and the age of the employees in the tested new ventures is between 35 and 40. More than one-third of employees are managers and over 86% of them have a degree of bachelor or above. The scores of the scale of the psychological state of new entrepreneurs are high. This shows that most of the new entrepreneurs have a high educational level, strong motivation for entrepreneurial success, and great self-confidence, which are essential in the process of innovative training. Therefore, the talent training of new entrepreneurial talents should be based on a high educational level and focused on practice.

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Gamified Assistance System: Effects of a Level and Feedback System on Work Performance, System Usability, and Motivation

Ulmer,

Braun,

Cheng

et al. 2024

Preprint

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Closed Loop Feedback Mechanism Effect Pilot Investigation on Manual Assembly Time and Process Variation

Cited by 3 publications

References 31 publications

A New Model for Determining Factors Affecting Human Errors in Manual Assembly Processes Using Fuzzy Delphi and DEMATEL Methods

A New Model for Determining Factors Affecting Human Errors in Manual Assembly Processes Using Fuzzy Delphi and DEMATEL Methods

Innovative Strategies of Training Mechanism of Higher Education for New Entrepreneurial Talents

Gamified Assistance System: Effects of a Level and Feedback System on Work Performance, System Usability, and Motivation

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