One-Fits-All vs. Tailor-Made: User-Centered Workstations for Field Assembly with an Application in Aircraft Parts Manufacturing

Mayrhofer, Walter; Rupprecht, Patrick; Schlund, Sebastian

doi:10.1016/j.promfg.2020.01.287

Cited by 25 publications

(4 citation statements)

References 11 publications

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“…Larger screens could help, although the worker's movement around the assembly position might still frequently leave the screens out of sight. This situation was reported by Mayrhofer et al [35]: a large overhead screen was installed on an aircraft part assembly line, but the worker had to move to retrieve the information because the screen was not visible from all angles and working positions. Neither do wide screens solve the need to move to the workbench to interact with the work instructions (validate, close instructions, go to following instruction, etc.…”

Section: Discussionmentioning

confidence: 91%

“…In a recent literature review, AR was identified as one of the two most promising technologies to support humans in manufacturing contexts, along with collaborative robots [33]. However, applications of AR are still in development and the technology has not reached full technological maturity [34,35].…”

Section: Literature Review 21 Some Considerations About Manual Assementioning

confidence: 99%

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Classification and Quantification of Human Error in Manufacturing: A Case Study in Complex Manual Assembly

2021

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Manual assembly operations are sensitive to human errors that can diminish the quality of final products. The paper shows an application of human reliability analysis in a realistic manufacturing context to identify where and why manual assembly errors occur. The techniques SHERPA and HEART were used to perform the analysis of human reliability. Three critical tasks were selected for analysis based on quality records: (1) installation of three types of brackets using fasteners, (2) fixation of a data cable to the assembly structure using cushioned loop clamps and (3) installation of cap covers to protect inlets. The identified error modes with SHERPA were: 36 action errors, nine selection errors, eight information retrieval errors and six checking errors. According to HEART, the highest human error probabilities were associated with assembly parts sensitive to geometry-related errors (brackets and cushioned loop clamps). The study showed that perceptually engaging assembly instructions seem to offer the highest potential for error reduction and performance improvement. Other identified areas of action were the improvement of the inspection process and workers’ provision with better tracking and better feedback. Implementation of assembly guidance systems could potentially benefit worker’s performance and decrease assembly errors.

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Section: Discussionmentioning

confidence: 91%

Section: Literature Review 21 Some Considerations About Manual Assementioning

confidence: 99%

Classification and Quantification of Human Error in Manufacturing: A Case Study in Complex Manual Assembly

2021

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“…The instructions can also be delivered using a light-guide system. In this case, using machine vision, overhead cameras can detect what the assembler is performing, and instructions can then be projected directly down onto the workspace or onto the object to be assembled using high-intensity projectors [39].…”

Section: Literature Reviewmentioning

confidence: 99%

Effect of Changes in the Sequence of Assembly Operations on Error Rates: A Case Study From the Car Manufacturing Industry

Real,

Torres

2024

IEEE Access

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Human operator-induced assembly errors affect the quality of car manufacturing. Understanding the factors influencing assembly errors is critical for quality improvement. The sequence of assembly operations, a factor markedly affecting cognitive load, remains largely understudied. We aimed to assess the effect of changing the sequence of assembly operations on error rates through four field experiments conducted in a car manufacturing plant. The parts (and errors) under study were child lock labels (missing labels), sunroofs (missing bolts), windshield wiper arms (loose bolts), and armrests (wrong selection). Parts were chosen based on data from quality records, and they represent different scenarios regarding the sequencing of assembly operations. Minitab was used to conduct the statistical test for two proportions at a significance level of 0.05. The experiments ran for a period varying from 9 to 25 weeks (22292 to 138456 cars). All four experiments exhibited significant differences in the proportion of errors. MODAPTS cycle-time calculations revealed no negative effect of assembly sequence variations on productivity. The study findings show that changing the assembly operation sequence can reduce the error rates, possibly due to the intermediary effect in reducing the operator's cognitive load. Overall, realizing quality improvement requires optimizing the assembly operation sequence in terms of time and productivity while considering its possible impact on error rates.INDEX TERMS Assembly systems, human factors, cognitive load, quality control, automobile manufacture.

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“…On a work organization level adaptations due to worker's fatigue and reliability (El Mouayni et al 2019), different performance levels and human limitations (d'Avella/Tripicchio 2020) are considered. User-centric and self-configured workstations that adapt to anthropometric characteristics of individual workers are described on a framework level in (Bortolini et al 2017), regarding specific personalization options in (Rupprecht/Schlund 2021), and by the example of an assembly system for aircraft parts in (Mayrhofer et al 2019).…”

Section: Research Backgroundmentioning

confidence: 99%

Towards Designing Adaptive and Personalized Work Systems in Manufacturing

Schlund¹,

Kostolani²

2022

Digitization of the Work Environment for Sustainable Production

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Adaptation of work to humans instead of humans constantly adapting to work systems and work environments has been a goal of ergonomics since the 19th century. To date, an actual adaptation of work to the specific features, conditions and requirements of individual users has so far only taken place in rudimentary form. The possibilities have now opened up by the advances of Cyber Physical Production Systems (CPPS). This enables a renewed attempt to implement the goal of adapting work systems to workers. Integration of advanced sensory skills into work systems within manufacturing allows better recognition of the work environment and the actual state of the system. Together with actuator capabilities, it enables adaptive work systems to adjust their structure and behaviour to the anthropometric and the cognitive features and requirements of the systems’ users. However, a framework that integrates the concepts of adaptivity and personalization into the work system model and work system design is still missing. This paper explores the roots of adaptive and personalized human-machine systems and shows a framework for integrating these concepts into work systems and manufacturing. Based on this, exemplary works and implementations of individual systems are presented and placed in the overall context. The focus is set on implementations within the TU Wien Pilot Factory that cover adaptability concepts on workplace, process, and system level.

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One-Fits-All vs. Tailor-Made: User-Centered Workstations for Field Assembly with an Application in Aircraft Parts Manufacturing

Cited by 25 publications

References 11 publications

Classification and Quantification of Human Error in Manufacturing: A Case Study in Complex Manual Assembly

Classification and Quantification of Human Error in Manufacturing: A Case Study in Complex Manual Assembly

Effect of Changes in the Sequence of Assembly Operations on Error Rates: A Case Study From the Car Manufacturing Industry

Towards Designing Adaptive and Personalized Work Systems in Manufacturing

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