Ergonomics Design Measures in Manual Assembly Work

Transcription

1 Ergonomics Design Measures in Manual Assembly Work Atiya Alzuheri 1, Lee Luong 2, and Ke Xing 3 School of Advanced Manufacturing and Mechanical Engineering, University of South Australia ¹alyaa002@students.unisa.edu.au ²Lee.Luong@unisa.edu.au ³Ke.Xing@unisa.edu.au ABSTRACT Manual assembly production systems are still the most viable method for production a variety of products in small to medium batches. However, manual assembly work is often associated with ergonomically poor conditions that result in Work Related Musculoskeletal Disorders WRMDs, which result in low productivity and quality problems. Yet ergonomics is not often considered sufficiently precise during the design phase of assembly systems. In addition, most of the studies relative to ergonomics in manual assembly systems have focused on only one single aspect of ergonomics human performance measures. This paper first identifies the most common ergonomics measures that can be used for quantitative evaluation of working postures and physical workloads in a manual assembly system to avoid WRMDs. The paper then propose a framework that allows for the consideration of multiple ergonomics measures to assess ergonomics stresses resulting from work postures in manual assembly work. Keywords: manual assembly, musculoskeletal disorder, productivity, quality, ergonomics measures 1. INTRODUCTION Nowadays, assembly enterprises are facing with highly competitive environment represent by increasing customization and shortening product lifecycle, with a high product variety produced in small batches [1]. Assembly systems that could fit these demands should be flexible and easily reconfigurable [2]. Intelligence and adaptability of human workers play a central role to make them the most flexible part of the assembling process of the product [3].Accordingly, there is essential need to understand the properties of work that are compatible with human worker capabilities and limitations [4]. The ergonomics discipline considers the physical and psychological of workers capacities as a main focus, as well as attempts to achieve improvements in technical and organizations domains [5]. With this context, it is desirable to adopt ergonomically sound design workstations and the surrounding work environment which guarantees the achievement of the objectives especially that considers productivity, integration, worker comfort, worker variety, and safety [6]. However, if ergonomics measures are neglected when designing and analysing of manual assembly systems, the industrial conditions can expose workers to the major risk of Work Related Musculoskeletal Disorders WRMDs [3]. In turn, disorders and illness consume considerable resources in manufacturing companies due to loss of competence, productivity and quality defects, as well as the replacement of staff and rehabilitation [5]. To avoid such negative consequences, efforts are set on integrating the appropriate ergonomics measures in the design of manual assembly systems [7]. 2. AIMS OF THE PAPER Through review of the literature on manual assembly systems, the first aim of this paper is to analyse the relationship between difficult postures associated with manual assembly work and ergonomics problems. These problems lead to the deterioration of worker performance, lower productivity and product quality deficiencies. Based upon this relationship, the second aim is to propose a special set of ergonomics measures to assess the work postural exposures of this assembly work. Conducting these proposed measures can identify the certain factors (e.g. the workers anthropometry, workstation design etc), that are important for designing a successful ergonomics assembly system with greater comfort, higher productivity, and better product quality. 3. THE NATURE OF MANUAL ASSEMBLY WORK 3.1 Manual Assembly Work Features In most industrial companies, manual assembly work is characterized by highly repetitive, short-cycled, monotonous, has little variation, and low personal control. Moreover, it is associated with low job satisfaction, high absenteeism and excessive mental and physical stress [8]. Furthermore, the workers of the system have little freedom in selecting their work content. They are almost never called on to make decisions, and almost never have an opportunity to plan their own activities [9]. These unsatisfactory conditions could be problematic for the scarce production resource in a manual assembly system, in short, was the worker [10]. In this context, much research has proposed basic

2 design rules or guidelines that give high consideration to avoid inadequate working postures during assembly tasks performing [11]. 3.2 Workers Postures in Manual Assembly Work Manual work in industrial assembly tasks include lifting, carrying, pushing, pulling of materials, and quality control. Sometimes such work is associated with heavy loads and high frequency. In general, this work involves postures that promote fatigue and discomfort like sustained static neck flexion, shoulder flexion, forearm muscle exertion, extreme wrist postures, and prolonged standing [12]. Assembly work is associated with the exposure mentioned above, often including the use of non-powered and/or power hand tools. In addition to that, it may have long cycle and excessive walking time including load carrying [8]. 4. OVERVIEW OF DEFICIENT ASSEMBLY ERGONOMICS 4.1 The Relationship between Working Postures of Assemblers and WRMDs Work under these circumstances is well-recognised as a major risk factor for the WRMDs such as cumulative trauma disorders, repetitive strain injuries, overuse injuries, and repetitive motion injuries [12]. However, each of these diagnostic terms attributed to certain types of occupational activity affect on the body parts and consequently causes those painful disorders. For example, in study of Hussain [13], a qualified assembly worker in a truck axle assembly reported through questionnaire, that they had been troubled with musculoskeletal disorders in one or more of the nine defined body regions during the one year as shown in table 1. Table 1: One year prevalence of musculoskeletal disorders in truck assembly workers by body part [13] Body part Musculoskeletal Disorders, n (%) Neck 194 (60) Shoulders 184 (57) Upper back 55 (17) Elbow 65 (20) Low back 211 (65) Wrists/hands 149 (46) Hips 26 (8) Knees 126 (39) Ankles/feet 42 (13) Total 255 (79) Low back disorders (LBDs), are the common symptom of all musculoskeletal disorders in people of working age, and are a major health and socioeconomic problem in companies. The risk of back failure increases for workers whose jobs include lifting with a rotated trunk. Also there is undoubtedly evidence that a low back pain is more common in workers whose jobs involve pushing and pulling. It is notable that the risk of shoulder injury is more likely to occur when the workers perform manual handling tasks with arms above shoulder level and pushing and pulling [14]. In addition, occupational disorders can occur if the manual workers have jobs which include extreme wrist extension, wrist flexion, high repetitive hand, and wrist motion. In a similar way, incidence of disorders indeed work related movement of other parts of upper extremities (i.e. neck, forearm, and arm) involve repetitive motion, awkward positions, vibrations, and forceful exertions [15]. Knee bending, walking, and lower-extremity tasks during assembly work are recognised as risk factors for knee disorders [16]. 4.2 The Influence of WRMDs on Productivity and Product Quality Data from the US Bureau of Labour and Statistics, pointed out that WRMDs in assembly workers in an increasing trend compared with other occupations [17]. US assembly companies spend untold billions dollars on lost productivity due to work related musculoskeletal disorders of workers. It can be expressed about it financially by the demands of worker compensation, insurance bills, law suits, and disability as well as the hiring and training of new staff. One of the most important characteristics of a product is its quality. It is a function of technological and human factors, and is greatly influenced by ergonomics variables such as work area, job design, equipment design, worker/workstation design, personal interaction, organizational structure, and work environment in its broadest sense [18]. Product quality is often directly linked to how effectively a worker can do his/her job. A number of empirical studies have identified the clear relationship between ergonomically problematic work tasks and the product quality in assembly work. In this regard, Lamkull [5] confirms that around 30 50% of all quality remarks in manual assembly environments are related to or directly owing to ergonomics problems. To solve the work related problems linked to health and safety encountered by manual assembly works, ergonomics has produced a large amount of requirements concerning appropriate design of the system elements in such a way that production system goals like improve productivity and better product quality can be realized without adverse affects for the workers [9]. 5. ERGONOMICS MEASURES IN MANUAL ASSEMBLY WORK In general, there is no universally agreed list of ergonomics measures can be intervened in the design of manual assembly systems to reach the known goals that mentioned earlier. Most of studies concerned with design process for the manual works in assembly

3 systems adapted ergonomics measures to identify the industrial environments factors which are to blame for problems associated with injuries [19]. The ergonomics measures in interventions at work in order to eliminate or reduce the incidence and prevalence of (WMSDs) classified as technical measures (i.e., engineering controls), organizational measures (i.e., administrative controls), or individual measures (i.e., individual training or education) [20]. According to the national academy of science [21], most of factors that may affect the risk of (WMSDs) in assembly process depend both on work procedures and workstation design. Accordingly, the measures that are considered in this paper are those categorized as technical measures. Several ergonomic measures (technical measures) for controlling the work design hazards have been attempted in manual assembly works, included the Lifting limitations according to NIOSH guidelinebiomechanical measure[22]; workers posture during the task according to OWAS guidelines-risk or injury measure [23]; metabolic energy consumption according to Garg guidelines-physiological measure[24]; cycle time from Methods Time Measurement MTM [25]; and Rapid Upper Limb Assessment-RULA [26], is a measure for risk factors associated with upper limb disorders. In forthcoming section a summary for these measures and existing studies and applications that underlie these measures as tools to quantify of risk factors in manual assembly tasks. 5.1 Biomechanical Strength Indication-NIOSH Lifting Equation: In 1991, the National Institute of Occupational Safety and Health NIOSH developed a new revised version of the NIOSH lifting equation as a biomechanical prediction models that uses task parameters to identify a Recommended Weight Limit RWL. The RWL is acceptable weight of lift which is believed to be safe for all healthy workers to handle over a period of time (up to eight hours). The algebraic expression of the 1991revised NIOSH lifting equation includes six multiplier factors to calculate the Recommended Weight Limit RWL: RWL = LC HM VM DM AM FM CM (1) Where LC is the Load Constant and is always equal to 23 kg. The load constant is the weight a worker should be able to lift once under ideal conditions at minimal risk. The other multiplier factors are the horizontal HM, vertical VM, distance DM, asymmetric AM, frequency FM, and coupling CM. A detailed description of the multiplier factors of the equation can be getting from the [22]. From the NIOSH perspective, the second part of the lifting equation is the Lifting Index LI. The LI is a relative estimate of the relative magnitude of physical stress associated with manual lifting tasks. A Lifting Index LI is then the actual weight lifted divided by the recommended weight limit: LI = Load Weight L / RWL (2) A lifting index score greater than 1.0 indicates potential hazard to most workers. The ultimate goal in redesigning the manual lifting jobs is to have a final LI score of less than 1.0 where all workers have adequate strength to perform the lifting task with a nominal risk of lower back injury. Studies [27, 28] used NIOSH lifting equation to evaluate the capacity of assembly workers in manual lifting tasks and to assist in the identification of ergonomics solutions for reducing the physical stress. 5.2 Categorical Postural Evaluation- OWAS: Postural analysis provides an analysis of the workers postures while working. The emphasis in this measure is on minimizing unnecessary worker actions and extreme postures will adversely impact energy expenditure and the strength and consequently which expose workers to WMSDs risks. In the OWAS (Ovako Working Posture Analysing System) observer makes an instantaneous analysis of worker postures according to a breakdown of work tasks and loads and defines it with a three digit code. The first digit describes the position of the back (four choices), second digit describes the arms (three choices), and the third digit describes the legs (seven choices). OWAS system based on expert judgments of the harmfulness of improper postures poor such as prolonged squatting, simultaneous trunk flexion and lateral bending at workplaces. A time-based sampling approach can be used with it so that the categorization can take account of the duration (time spent in particular posture). The workers postures calculated in percentages and assigned an action category code. Action Categories AC classify the relative risk and urgency for intervention to prevent musculoskeletal disorders due to exposure, especially to Low Back Pain LBP. OWAS does not have any kind of underlying mathematical model. Instead it relies on a lookup table that converts three digit posture codes into action categories. Table 2 converts the action category into action requirement. Table 2: The OWAS action code [23] Action Category Action Required AC1 No action required AC2 Action required in the near future AC3 Action required as soon as possible AC4 Action required immediately The application of the OWAS system, enable to acquire ergonomics data for the examined tasks and usefully

4 diffuse, like already happens in the studies of [3, 29], in the assembly activities. 5.3 Physiological Assessment-Metabolic Energy Expenditure: Metabolic energy expenditure is the physiological measurement which has been suggested for determining the amount of energy requirement needed to perform a given work without accumulating an excessive amount of physical fatigue. The metabolic prediction model is based on the assumption that a job can be divided into tasks or activity elements, where activities are carefully categorized and their duration monitored. The energy expenditure requirements for each task can be added together to determine the energy expenditure of the whole job. It is possible to measure energy expenditure of the tasks by using prediction equations derived from empirical data. It requires accounting for all information s for each task to compute these energy requirements. This information s include the following factors; force exerted, distance moved, frequency, task posture, lifting technique for lifting tasks (if the task requires that), and the time needed to perform the tasks. Age, sex, height, and weight, three worker factors, are also needed to taking into account. The prediction model is described by the following equation adapted from Garge guideline to estimation of metabolic rate: E job = E basal + Σ (E taskj T taskj ) (3) Where E job = average energy expenditure rate of the job (Kcal/min), E basal = metabolic energy expenditure rate necessary to maintain basal metabolism and posture (Kcal/min), E taskj = net metabolic energy expenditure of the j th task in steady state (Kcal), T taskj = time duration of the j th task (min.). Since assembly tasks involve mostly object work from one place to another represents the most important factor causing variation of energy expenditure among assemblers, a number of studies have estimated energy expenditure of different assembly tasks [30, 31]. 5.4 Methods Time Measurement- MTM: Predetermined Time Standard Systems PTS is used as a field of work measurement to estimate the time needed by well-trained industrial worker to perform a particular task at a specified level of performance. The systems set the standard time based on the motion used, their nature, the condition under which they occur, and their previously determined performance time. One of the most well known PTS is Method Time Measurement MTM, which divides any operation into a set of single basic motions. MTM-1, the most detailed PTS, consists of 7 categories of actions (Obtain, Locate, Rotate, Force, Recoil, Visual and Body) containing 26 single motions that are used to describe manual activities. Each of these constituent basic movements has a predetermined time value as a function of variables acting upon it. Adding up the times assigned for each movement gives the total time to complete a certain task. This total time represents the average production time interval. For this purpose, MTM can be considered most appropriate as an indicator for the labour productivity [30, 32]. 5.5 Rapid Upper Limb Assessment-RULA: The Rapid Upper Limb Assessment RULA algorithm is applied commonly to evaluate the exposure of workers to the risk of upper limb disorders. RULA examines risk factors of upper limb disorders based on working posture, static muscle work, the weight of loads, force, time worked without a break, and repetition. The combination of these factors results a final score, rating of 1 7. The value of score determines if the task has a risk of an upper limb Injury. The score can be compared with the list of four action levels, which are proposals for more detailed investigations based upon the severity of the score. A summarization of the action levels and the actions that should be taken when scores of a task fall into one of these categories is presented in Table 3. Researchers [33, 34] used RULA in comparing existing and proposal assembly workstation designs a part of justification or proposal for ergonomics changes. Table 3: RULA posture score, action level with relevant proposals investigations [26] Action level RULA Score Proposals Investigations Most comfortable, if it is not repeated for long periods Further investigation and correction needed and changes may be required Investigation and changes are required soon 4 7+ Changes required immediately toward the improvement of the task and avoid any injuries 6. DISCUSSION Insight into the effectiveness of ergonomics measures and implementation in research work confirmed that these are mostly focused on a single ergonomics aspect of human worker [35, 36]. This is a limitation in assessment of ergonomics stress level in work situations due to the following reasons: The possible interactions between more than one measure that may lead to conflicting conclusions

5 about certain work hazards for the assemblers if these measures are considered separately. The large number of postures and the different exposures during manual assembly operations (as mentioned earlier) that should be considered in ergonomics evaluation. The proposed ergonomically measures are sensitive to changes in the physical structure of workstations and workplaces in assembly systems. Consequently, the evaluation process by more than one measure is justified to use for sufficiently precise for characterising ergonomics conditions of various work activities during manual assembly works. Also, use of multiple introduced ergonomics measures without optimising interest would generally lead to unrealistic solutions, especially when conflicting conclusions are present. Guarantees the optimal solution to design of system elements to avoid the negative consequences of WRMDs, can be generate via a tradeoff between the selected ergonomics measures and also other considerations (if it s found) like economic in one of solutions. In this situation we may first want to combine all of the individual measures into a single objective function. This function (e.g. desirability function [37]) represents the decision-maker s preferences. Following that, applying a gradient search technique like Response Surface Methodology RSM or Genetic Algorithms GA to find the optimum value of the assessed function. 7. CONCLUSIONS Review of the literature dedicated to work involving manual assembly works, strongly emphasized that the design of an assembly system directly affects the physiological and ergonomics functions of workers. Also results were reported regarding related literature, the assembly system design can be developed concurrently with ergonomics, physiology, and safety issues by interventions of ergonomics measures while the system is still in its early design stage or during rebuilding projects. This paper lists the most common ergonomics measures for evaluating working postures and physical workloads in a manual assembly system to avoid WRMDs, such as NIOSH, OWAS, expenditure energy, MTM, and RULA. These measures generate data on the postures adopted and physical load experienced during manual work. The data can be used to analyse assembly tasks for risk of important ergonomics and physiological stressors that affect workers. The main conclusion reached, most of studies considered manual assembly systems focus on only single aspects of ergonomics human performance measures. Conduct separate analysis along with postural and loading effects on the body may lead to conflicting conclusions due to the possible interactions between different measures. This current gap may be bridged by taking into account multiple measures to assess ergonomics stresses resulting from work postures. 8. FURTHER WORK This work is part of the research considering novel approach to assembly system so-called linear walking worker, where fitters travel along the line carrying out each assembly task at each workstation. Due to needs for highly demand time period to achieve multi-task assembles with repetitive motion movements, the implementation of walking worker assembly systems in the manufacturing industry may have negative effects on worker attitudes. These attitudes can include; presence of WRMDs risk factors, and reduced output per worker. 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