Quality Inspection Task in Modern Manufacturing

The development of numerically controlled machines, group technology, cellular manufacturing and just-in-time (JIT) production systems have revolutionized the way products are designed and manufactured. These technological and strategic advances have changed the role of human operators in the manufacturing environment. The highly specialized work force of the low-tech manufacturing system has evolved into the multi-skilled work force of the high- tech manufacturing system. Among the multiple tasks that an operator is expected to perform in advance manufacturing systems (AMS) are job scheduling, inventory planning, machine set-up, problem-solving and quality inspection. Throughout this evolution, human sensory detection capabilities have been a vital but often ignored component of the quality inspection task. Although automation is often employed to construct and assemble products within AMS, most inspections and quality checks are still done by human operators due to the inherent problems in machine vision and decision-making. While humans remain responsible for inspection, it has been widely accepted that the quality inspection task performed by humans is prone to error. Some studies indicate human inspectors typically find only ~80% of the defects. Despite the contributions of human factors research to the understanding of human performance in the quality inspection task, the manufacturing trend has been to design quality schemes that compensate for poor inspector performance instead of trying to improve it (Drury 1992)

Risk of injury analysis in depth jump and squat jump

Introduction: The depth jump (DJ) and squat jump (SJ) are accepted ways to assess and train power producing ability but are not without risk of injury. Methods: Sixteen male participants (age = 21.7 ± 1.54 yrs., height = 177.7 ± 11.4 cm, mass = 77.7 ± 13.6 kg) were evaluated for power exertion capabilities while being assessed for risk of injury in the knee and low back through a range of resistances based on a percentage of participants’ heights in the DJ (0% through 50%) and bodyweights for the SJ (0% through 100%). Two variables were used to assess the risk of injury in the knee: valgus angle and internal abduction moment (IAM). Four variables were used in the low back: compression and shear force at the L5/S1 vertebrae, intra-abdominal pressure (IAP), and erector muscle tension. Results: With increasing DJ drop height, participants showed increased risk of injury in the knee through the valgus angle and IAM. In the low back, significant correlation occurred between increasing drop height and the shear force and IAP while compression force and erector muscle tension were more correlated with the power exertion of the participants than the drop height. With increasing SJ resistance, no significant increased risk of knee injury was detected. However, all low back variables except the IAP were significantly influenced by the increased resistance. Conclusion: Risk of injury in the knee and low back can be strongly dependent not only on the type of jump, but also the amount of resistance. The resulting power exerted by the athlete can also influence the risk of injury

Risk of injury analysis in depth jump and squat jump

Introduction: The depth jump (DJ) and squat jump (SJ) are accepted ways to assess and train power producing ability but are not without risk of injury. Methods: Sixteen male participants (age = 21.7 ± 1.54 yrs., height = 177.7 ± 11.4 cm, mass = 77.7 ± 13.6 kg) were evaluated for power exertion capabilities while being assessed for risk of injury in the knee and low back through a range of resistances based on a percentage of participants’ heights in the DJ (0% through 50%) and bodyweights for the SJ (0% through 100%). Two variables were used to assess the risk of injury in the knee: valgus angle and internal abduction moment (IAM). Four variables were used in the low back: compression and shear force at the L5/S1 vertebrae, intra-abdominal pressure (IAP), and erector muscle tension. Results: With increasing DJ drop height, participants showed increased risk of injury in the knee through the valgus angle and IAM. In the low back, significant correlation occurred between increasing drop height and the shear force and IAP while compression force and erector muscle tension were more correlated with the power exertion of the participants than the drop height. With increasing SJ resistance, no significant increased risk of knee injury was detected. However, all low back variables except the IAP were significantly influenced by the increased resistance. Conclusion: Risk of injury in the knee and low back can be strongly dependent not only on the type of jump, but also the amount of resistance. The resulting power exerted by the athlete can also influence the risk of injury

Assessment of Slip Severity Among Different Age Groups

A laboratory study utilizing new techniques for assessing slip severity was conducted to investigate the process of inadvertent slips and falls among different age groups. Forty-two subjects from three age groups (young adults, middle-aged, and the elderly) walked on a rectangular track at a self-determined pace. Without the subjects’ awareness, a slippery floor surface was placed on the track over a force-measuring platform. The results indicated that elderly adults’ friction demand (RCOF) was not significantly different from the young and middle-aged adults. The older adults, however, fell more often than the other age groups. Fall recovery threshold (FRT) measures indicated that younger adults were able to recover from a slip (thus preventing a fall) with higher sliding speeds and longer slip distances than older adults. Additionally, older adults’ adjusted friction utilization (AFU) on the slippery floor surface was not adjusted within the dynamic friction requirements, resulting in more falls. Based on the age-related differences observed, it appears that fall-related accidents among older adults are due more to factors influencing compensation of a slip rather than gait characteristics influencing slip initiation

Effects of Aging on the Biomechanics of Slips and Falls

Although much has been learned in recent decades about the deterioration of muscular strength, gait adaptations, and sensory degradation among older adults, little is known about how these intrinsic changes affect biomechanical parameters associated with slip-induced fall accidents. In general, the objective of this laboratory study was to investigate the process of initiation, detection, and recovery of inadvertent slips and falls. We examined the initiation of and recovery from foot slips among three age groups utilizing biomechanical parameters, muscle strength, and sensory measurements. Forty-two young, middle-age, and older participants walked around a walking track at a comfortable pace. Slippery floor surfaces were placed on the track over force platforms at random intervals without the participants’ awareness. Results indicated that younger participants slipped as often as the older participants, suggesting that the likelihood of slip initiation is similar across all age groups; however, older individuals’ recovery process was much slower and less effective. The ability to successfully recover from a slip (thus preventing a fall) is believed to be affected by lower extremity muscle strength and sensory degradation among older individuals. Results from this research can help pinpoint possible intervention strategies for improving dynamic equilibrium among older adults

Digital Human Models for Ergonomics

Digital human models in the context of this section are computer-generated representations of human beings used in computer-aided design (CAD) or similar programs. These models are increasingly being used by ergonomists and other engineers to design both equipment and work environments to meet the needs of human operators. They have the advantage of allowing the designer to explore the potential advantages and disadvantages of different design configurations without requiring the construction of expensive physical mock-ups used in the past. Using a digital human model, design engineers can position and manipulate operators of varying anthropometry within the simulated work environment. A variety of different analyses can be performed depending on the sophistication of the computer package. Currently available analysis modules include: reach and clearances, field of vision and visual obstructions, work posture and biomechanics, metabolic energy expenditure, time and motion, and others. In addition, the ability of these models to dynamically simulate human operators within proposed engineering projects has become a popular presentation and sales tools

Design of Visual Displays for Teleoperation

Human exposures to hostile work environments can be reduced when tele-operated systems are used to remotely control manipulators in these environments. Tele-operation systems were initially developed by the nuclear industry but are currently applied in areas including surgery, construction, mining, warehousing, firefighting, undersea exploration, military operations, and space. The role of human operators in tele-operated systems varies with the level-ofautomation of the system. Some systems require only supervisory control from the operator, while many others require direct manual manipulation through a controller. However, even for highly automated systems, human operators play an important role as a backup when the system fails. Telepresence can be achieved through sensing appropriate information about the tele-operation task environment, and providing this information to the human operator at the remote site (Sheridan 1992). A great deal of human engineering information concerning the design of workstations for telerobotic systems is closely related to meeting telepresence requirements. In this regard, human depth perception (as a third dimension) based on the information provided by the two-dimensional (2D) surface of a video display terminal (VDT) very much determines the quality of a tele-operation system

Models in Manual Materials Handling

The ergonomics approach to manual materials handling (MMH) tasks defines a Man-Task-Environment System. A generally accepted means of minimizing MMH related injuries is to design MMH tasks so that the demands of the tasks are less than the capacities of the individuals performing these tasks. Task design is dependent, in part, on the availability of comparable data for task demands and worker capacities. The generation of the appropriate data is dependent, in part, on being able to identify the pertinent capacity parameters of manual materials handling activities. In the past, a substantial effort has been directed at determining ‘safe’ lifting capacities for individuals and groups of individuals. The assumption used for these studies was that there is a relationship between an individual’s capacity and his or her injury potential. In other words, a person with a small capacity with respect to a given task demand is more likely to be injured than another person with larger capacities. For the measurement of a safe and permissible lifting capacity three approaches are commonly used. The first approach is the biomechanical approach, the second approach is the physiological approach, and the third is the psychophysical approach. These three approaches and the models developed using the selected criterion under each approach are discussed below

The Effects of Multitasking on Quality Inspection in Advanced Manufacturing Systems

Although the industrial quality inspection task has been extensively studied, the effect of multitasking on the performance of the operator in a hybrid inspection system is still unknown. The experiment described in this article compared the quality inspection performance for participants performing a single task, 3 multiple tasks, and 5 multiple tasks. The results of this research indicate that the performance of the operator in the quality inspection task while multitasking in an advanced manufacturing system will be determined by the interaction between the number of different types of defects that can be presented at the same time in the inspected parts and multitasking. The best performance will be obtained when the load created by additional tasks minimizes the monotony of the quality inspection task without interfering with the processing resources needed for the memorized quality criteria