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Unnatural working postures usually cause musculoskeletal problems for workers in work field, especially in traditional industry. Many analysis and survey methodologies have been developed to identify unnatural postures and disorder risks in workplaces. The Ovako Working Posture Analyzing System (OWAS) and Nordic Musculoskeletal Questionnaire (NMQ) are the representative methods and applied widely. This study applied the both tools to investigate the work field of a manufacturing factory of the water heater’s case. We divided the manufacturing process into nine workshops, took the pictures of working motions by DV camera and analyzed the postures on OWAS. From the OWAS results, we could identify the risks level of musculoskeletal symptoms as four Action Categories (AC). And from the comparison of OWAS and NMQ results, we could provide the suggestions to improve the working methods and environment. From the results of OWAS, we found that the operators) head/neck and back were above AC3 in some workshops. If the situation continued in long period, the operators might have the risk to get musculoskeletal symptoms. From the investigation of NMQ, we also found that the percentage of aches on neck, shoulders and lower back were higher than other parts of body. The correlation between aches and jobs was more than 75 per cent. So we provided some suggestions to improve: work rotation and adjustment of work surface/height to fit in with Ergonomics. Then the risks of musculoskeletal symptoms would be reduced.

Facility structures in liquefied natural gas (LNG) plants require tremendous amounts of scaffolding to facilitate relevant industrial operation and maintenance. As such, the productivity of scaffolding operations in turnaround maintenance (TAM) has attracted much attention in recent years. In addition, health and safety issues have been recognised as a key contributor along with productivity improvement in the LNG industry. This study aims to integrate work posture analysis into value stream mapping to achieve an optimised and balanced improvement in both productivity and health and safety.

A case study approach is adopted to integrate lean and work posture analysis in a TAM site. The lean improvement is conducted through value stream mapping, and the work posture analysis is conducted through the Ovako Working Posture Analysis System method. A three-step optimisation strategy is then developed for achieving optimised performance in waste reduction and work posture improvement.

It is found that the implementation of value stream mapping can help eliminate waste in the installation process, therefore eliminating potential health and safety risks. However, health and safety of onsite workers does not always improve as lean implementation intensifies. There is an optimised erection schedule that has the lowest health and safety risk within a waste reduction target.

In contradiction to previous studies, which rely on qualitative assessment to identify the a positive correlation between lean and health and safety, this study reveals the distinct difference between lean attributes and health and safety attributes through a quantitative assessment and is more readily to be implemented at the site level for simultaneous improvement in lean and health and safety.

The purpose of this paper is to comparatively examine the personnel working in the clothing sector by examining them in three different methods in order to determine the working postures, identification of the stress factors of musculoskeletal system and the exposures depending on the working postures. Methods used in the study, REBA (Hignett and McAtamney, 2000), Ovako Working Posture Analyzing System (OWAS) (Karhu et al., 1977) and PLIBEL (Kemmlert, 1995) are the scientific observation-based methods. Within the scope of this study, the working stations and the working postures of the operators who work in the clothing sector were examined and their movements that could cause harm to the body were examined and in conclusion some suggestions were suggested to prevent these movements.

Due to the standard unit of times in clothing sector are short and the work done is very repetitive, 30 min recording was thought as enough for each operator examined. These recorded videos were then divided into 30 s photographs to obtain the poses of the operators’ working postures. In the scope of the research, first, the PLIBEL observation form was filled as the PLIBEL method is more general one. According to the working postures, the body regions which are damaged or can be damaged were identified and the PLIBEL form was filled in the consideration of the risk factors in the form (Malchaire 2011). In addition, the photographs were also analyzed with REBA and OWAS methods for having more quantitative and detailed results.

The working postures of the operators who work in the cutting, sewing, ironing, quality control and packaging departments of six clothing companies were examined in the scope of this research with PLIBEL, REBA and OWAS methods in terms of ergonomy. The results belonging to each department were given separately. REBA and OWAS methods have been applied in order to investigate the working postures in more detail due to the lack of providing numerical data of the PLIBEL method. The reliability of the study has been approved with obtaining the similar results from the REBA and OWAS methods. According to Table VIII, both of the methods show that all the departments in question need ergonomic arrangements. It was analyzed that the cutting department is in the first place which needs ergonomic arrangement immediately (REBA %90.58, OWAS %87.69).

This study is composed of 65 operators who have experience between 5 and 22 years and in the age range of 22–43 working in the cutting, sewing, ironing, quality control and packaging departments in eight different clothing companies. These 65 operators were recorded by video camera during their work. The recording time were selected randomly. The movements of operators during their own work have been taken into consideration.

This paper indicates the usability of the PLIBEL, OWAS and REBA methods in clothing sector. Using these methods in clothing sectors states the value and the originality of this paper.

The purpose of this paper is to demonstrate three techniques to extract human factor information from specific railway maintenance tasks. It describes the techniques and shows how these tools can be applied to identify improvements in maintenance practices and workflow.

Three case studies were conducted on single group of technicians (n=19) at a railway maintenance workshop in Luleå, Sweden. Case study I examined the posture of the technicians while they were changing the brake shoes of freight wagons; the study employed the Standard Nordic Questionnaire and a videotape using the Ovako Working Posture Analysis System (OWAS). Case study II looked at maintenance repair times required to change the wheel axle on freight wagons at the workshop. A video filming method suggested by the European Agency for Safety and Health at Work was used to measure actual maintenance time. Finally, case study III considered the technicians’ (n=19) perception of work demands, their control over the work and their social support while performing maintenance tasks (brake shoe and wheel axle maintenance); to this end, the case study used a demand control support questionnaire.

In the first case study, the Standard Nordic Questionnaire confirmed that technicians at this particular railway vehicle maintenance workshop suffer from back and shoulder pain. The Ovako Working Posture Analysis showed that 21 percent of the working time required to fit the brake wedge and cotter pin fits into two OWAS categories: category 3, where “change is required as soon as possible,” and category 4, where “change is required immediately”. Problems stem from poor workplace layout, incorrect posture and inaccessibility of tools and components. In the second study, the video analysis indicated that the working time to change the wheel axle of a freight wagon is greatly affected by poor workplace layout. The third case study showed that the technicians have lower “psychological demands” (mean=13), “higher control over work” (mean=16) and “high social support” (mean=22).

The objective of this study was to apply knowledge about human factors to the functional relationships between maintenance personnel, tasks and the working environment to improve safety. If the workplace layout, working posture, maintenance manuals and accessibility of tools are poorly planned, maintenance performance can be adversely affected. The results of this study should assist maintenance management to design new policies and guidelines for improving the work environment.

Three case studies were conducted at a railway maintenance workshop in Luleå, Sweden, to collect data on how human factors affect various railway maintenance tasks.

Based on virtual maintenance, this paper aims to propose a time prediction method of assembly and disassembly (A&D) actions of product maintenance process to enhance existing methods’ prediction accuracy, applicability and efficiency.

First, a framework of A&D time prediction model is constructed, which describes the time prediction process in detail. Then, basic maintenance motions which can comprise a whole A&D process are classified into five categories: body movement, working posture change, upper limb movement, operation and grasp/placement. A standard posture library is developed based on the classification. Next, according to motion characteristics, different time prediction methods for each motion category are proposed based on virtual maintenance simulation, modular arrangement of predetermined time standard theory and the statistics acquired from motion experiment. Finally, time correction based on the quantitative evaluation method of motion time influence factors is studied so that A&D time could be predicted with more accuracy.

Case study of time prediction of products’ various A&D processes is conducted by implementing the proposed method. The prediction process of diesel cooling fan disassemble time is presented in detail. Through comparison, the advantages and effectiveness of the method are demonstrated.

This paper proposes a more accurate, efficient and applicable product A&D time prediction method. It can help designers predict A&D time of a product maintenance accurately in early design phases without a physical prototype. It can also provide basis for the verification of maintainability, the balance of the design of product structure and system layout.

This paper aims to perform the real-time and accurate ergonomics analysis for the operator in the manual assembly, with the purpose of identifying potential ergonomic injuries when encountering labor-excessive and unreasonable assembly operations.

Instead of acquiring body data for ergonomic evaluation by arranging many observers around, this paper proposes a multi-sensor based wearable system to track worker’s posture for a continuous ergonomic assessment. Moreover, given the accurate neck postural data from the shop floor by the proposed wearable system, a continuous rapid upper limb assessment method with robustness to occasional posture changes, is proposed to evaluate the neck and upper back risk during the manual assembly operations.

The proposed method can retrieve human activity data during manual assembly operations, and experimental results illustrate that the proposed work is flexible and accurate for continuous ergonomic assessments in manual assembly operations.

Based on the proposed multi-sensor based wearable system for posture acquisition, a real-time and high-precision ergonomics analysis is achieved with the postural data arrived continuously, it can provide a more objective indicator to assess the ergonomics during manual assembly.

The use of shoulder protectors is strongly recommended when carrying objects on the shoulder to ensure the health and safety of workers. Thus, this study aimed to develop and verify an ergonomic shoulder protector that considers human body shape and carrying posture from an ergonomic perspective. Ultimately, this study will present a shoulder protector with enhanced fit and safety for carrying workers at construction sites.

The shoulder protector was designed and printed using three-dimensional printing technology with variable side neck points and shoulder point heights to reflect the human body's shoulder line shape and to position the carried object stably on the shoulder. The developed shoulder protectors were evaluated in terms of their fit according to the work posture of the carrier, adherence upon motion and durability through structural analysis.

The design of the shoulder protector for carrying workers followed the shoulder line. It is best placed above the side neck point by 1.0 cm and above the shoulder point by 2.0 cm. Its length is slightly shorter than the human shoulder for superior fit and safety.

The final shoulder protector (FSP) for carrying workers reflects the body curvature while enhancing fit and safety by considering activity and protective factors. As functional studies and evaluations on the need for protectors are scarce, this study provides fundamental data in the evaluation of protective gears.

Carpenters are constantly vulnerable to musculoskeletal disorders. Their work consists of subtasks that promote nonfatal injuries and pains that affect different body segments. The purpose of this study is to examine ergonomic exposures of carpentry subtasks involved in floor framing, how they lead to musculoskeletal injuries, and how preventive and protective interventions around them can be effective.

Using wearable sensors, this study characterizes ergonomic exposures of carpenters by measuring and analyzing body movement data relating to major subtasks in carpentry flooring work. The exposures are assessed using Postural Ergonomic Risk Assessment classification, which is based on tasks involving repetitive subtasks and nonstatic postures.

The findings of this paper suggest severe risk impositions on the trunk, shoulder and elbow as a result of the measuring and marking and cutting out vent locations, as well as in placing and nailing boards into place.

Because of the type and size of wearable sensor used, only results of risk exposures of four body-parts are presented.

This study draws insights on how to benchmark trade-specific measurement of work-related musculoskeletal disorders. Safety efforts can be targeted toward these risk areas and subtasks. Specifically, results from these will assist designers and innovators in designing effective and adaptable protective interventions and safety trainings.

Extant studies have failed to provide adequate evidence regarding the relationships between subtasks and musculoskeletal disorders; they have only mimicked construction tasks through laboratory experimental scenarios. This study adds value to the existing literature, in particular by providing insights into hazards associated with floor carpentry subtasks.

The physically-demanding and repetitive nature of construction work often exposes workers to work-related musculoskeletal injuries. Real-time information about the ergonomic consequences of workers' postures can enhance their ability to control or self-manage their exposures. This study proposes a digital twin framework to improve self-management ergonomic exposures through bi-directional mapping between workers' postures and their corresponding virtual replica.

The viability of the proposed approach was demonstrated by implementing the digital twin framework on a simulated floor-framing task. The proposed framework uses wearable sensors to track the kinematics of workers' body segments and communicates the ergonomic risks via an augmented virtual replica within the worker's field of view. Sequence-to-sequence long short-term memory (LSTM) network is employed to adapt the virtual feedback to workers' performance.

Results show promise for reducing ergonomic risks of the construction workforce through improved awareness. The experimental study demonstrates feasibility of the proposed approach for reducing overexertion of the trunk. Performance of the LSTM network improved when trained with augmented data but at a high computational cost.

Suggested actionable feedback is currently based on actual work postures. The study is experimental and will need to be scaled up prior to field deployment.

This study reveals the potentials of digital twins for personalized posture training and sets precedence for further investigations into opportunities offered by digital twins for improving health and wellbeing of the construction workforce.