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Remote operation of continuous mining machines has enhanced the health and safety of underground miners in many respects; however, numerous fatal and non-fatal continuous miner struck-by accidents have occurred. In an effort to prevent these injuries, NIOSH researchers at Pittsburgh Research Laboratory studied the workplace relationships between continuous miner operators and various tramming tasks of the equipment using motion capture data, operator response times, and field of view data to evaluate the factors influencing operator-machine struck-by events (contact with a solid object) in a virtual mine environment. It is not feasible (nor ethical) to use human subjects to directly evaluate factors that precipitate such injuries. However, use of motion analysis data and digital human models can facilitate analysis of struck-by accident risk by allowing investigators to manipulate factors that influence injury.

This paper discusses the application of digital human models (DHM) to examine computer generated forces necessary to move specific joysticks by using roof bolter virtual operators to predict the forces experienced on the operator's upper extremities. Using DHM and simulations of static movements, investigators analyzed predictions of joint moment and joint force effects on virtual operator's right wrist, elbow and shoulder and compared them to different body dimensions and work postures. This study exemplifies the ease of estimating upper extremity loads on equipment operators using virtual operators and computer models of equipment and work environment. As expected, comparing results of percentage of joint force and moment reduction using the electronic control and of the mechanical control showed that the electronic control had lower joint forces and joint moments over the mechanical control.

NIOSH researchers conducted a study to evaluate the severity of muscle recruitment and spine loads resulting from performance of the roof bolting cycle in different work postures and mine seam heights. Ten male and two female subjects performed three repetitions of a mine roof bolting in each of seven posture/seam height combinations, while researchers obtained motion data of their actions using a motion capturing system. A database containing forces on L4/L5 spinal joint and on back muscles was generated by processing the captured motions from each subject using UGS PLM Solution Jack software’s task analysis toolkit – lower back analysis. An analysis of variance was performed using the maximum values for spinal forces and moments and estimated muscle forces for ten trunk muscles in the resulting database.

This paper presents the results of an effort to verify a simulation designed to investigate the safe speed range for the vertical movement of roof bolter boom- arm to reduce worker injuries in underground coal mines. The results of the laboratory investigations are being used to (1) determine input parameters unique to the mining environment and needed to develop a credible, computer-based, human-machine interactive model (2) confirm the model would accurately represent operator movements and positions while performing his tasks relative to the roof bolter and (3) determine which aspects of the procedure being simulated are most critical if hazard predictions are to be made from simulations using valid models of operators' behaviors and varying the machine appendage speed.

This paper presents the results of a study using computer human modeling to examine machine appendage speed. The objective was to determine the impact of roof bolter machine appendage speed on the likelihood of the operator coming in contact with. A contact means two or more objects intersecting or touching each other, e.g., appendage makes contact with the operator’s hand, arm, head or leg. Incident investigation reports do not usually contain enough information to aid in studying this problem and laboratory experiments with human subjects are also not feasible because of safety and ethical issues. As an alternative, researchers developed a computer model approach as the primary means to gather data. By simulating an operator’s random behavior and machine’s appendage velocity, researchers can study potential hazards of tasks where it is not possible to perform experiments with human subjects.

This paper presents the results of a study to verify and validate a computer model that represents and analyzes motions and hazardous events in a simulated three-dimensional workplace. The purpose of the computer model is to support research that is investigating the safe speed range for the vertical movement of roof bolter boom arms to reduce worker injuries in underground coal mines. The information obtained for this paper is based upon a project that is investigating means to reduce workers risks of injury from exposure to mining machinery. The methodology being employed by the project includes human factors design considerations, anthropometric modeling and simulation tools, laboratory validation, engineering interventions, and collaboration with industry and an equipment manufacturer.

This paper presents an approach for representing and analyzing random motions and hazardous events in a simulated three-dimensional workplace, providing designers and analysts with a new technique for evaluating operator-machine interaction hazards in virtual environments. Technical data in this paper is based upon a project striving to reduce workers’ risks from being hit by underground mining machinery in a confined space. The project’s methodology includes human factors design considerations, ergonomic modeling and simulation tools, laboratory validation, and collaboration with a mining equipment manufacturer. Hazardous conditions can be analyzed in virtual environments using collision detection. By simulating an operator’s random behavior and machine’s appendage velocity, researchers can accurately identify hazards, and use that information to form safe design parameters for mining equipment.