Truck and shovel are the most common raw material transportation system used in the cement quarry operations. One of the major challenges associated with the cement quarry operations is the efficient allocation of truck and shovel to the mining faces. In order to minimize the truck and shovel operating cost, subject to quantity and quality constraints, the mixed integer linear programing (MILP) model for truck and shovel allocation to mining faces for cement quarry is presented. This model is implemented using the optimization IDE tool GUSEK (GLPK under SciTE Extended Kit) and the GLPK (GNU Linear Programming Kit) standalone solver. The MILP model is applied to an existing cement quarry operation, the Kohat cement quarry located at Kohat (Pakistan) as a case study. The analysis of the results of the relating case study reveals that significant gains are achievable through employing the MILP model. The results obtained not only show a significant cost reduction but also help in achieving a better coordination among the quarry and quality department.

The present paper studies the whole body vibration of a three-axle dump truck during various operational conditions in Zonuz Kaolin Mine of Iran. At first, the root mean square of vibrations at different speeds, as well as in payloads and distribution qualities of materials in the truck dump body and also on different haul road qualities are experimentally obtained. Then, the vibrational health risk in all operational conditions is statistically analyzed based on ISO 2631-1 standard. As a result of this analysis, an optimization problem is constructed and solved to obtain the optimum operating conditions of the truck. In the proposed problem, at first, regression analysis in terms of RMS of vibrations and truck speed is applied. Then, the total RMS at the consequential working phases of the truck is minimized in the presence of some constraints related to the health risk and productivity levels. Solving the proposed constrained optimization problem determines the optimum payload and truck speed in various conditions to keep materials hauling at the lowest possible vibrational health risk level while the mine productivity at the planned level remains.

Fuzzy Logic is one of the concepts that has created different scientific attitudes by entering into various professional fields nowadays and in some cases has made remarkable effects on the results of the practical researches. However, the existence of stochastic and uncertain situations in risk and accident field, affects the possibility of the forecasting and preventing the occurrence of the accident and the undesired results of it.In this paper, fuzzy approach is used for risk evaluating and forecasting, in accidents caused by working with vehicles such as lift truck. Basically, by using fuzzy rules in forecasting various accident scenarios, considering all input variables of research problem, the uncertainty space in the research subject is reduced to the possible minimum state and a better capability of accident forecasting is created in comparison to the classic two-valued situations. This new approach helps the senior managers make decisions in risk and accident management with stronger scientific support and more reliably.

Background and Objectives: Exposure to vibration is one of the occupational agents that causes a variety of health effects. The aim of this study was to determine the association between exposure to human vibration and physical performance of mining drivers. Methods: In the present study, 65 drivers working in one of the Iron Ore mines, were asked to complete the standard questionnaire for assessing the level of disability of the arm, shoulder and hand (DASH). Exposure to human vibration was measured using Svantek 106 vibrometer. Drivers' physical performance was assessed based on grip strength, Pegboard dexterity, and monofilament finger sensory tests. Data were analyzed using SPSS 21 software. Results: The average vibration acceleration whole body (WBV) and hand-arm (HAV) were 1. 00± 0. 23 and 2. 46± 0. 68 m/s 2 respectively. There was a significant relationship between exposure to HAV and the grip strength and hand dexterity (p <0. 05). According to the DASH score, 56. 9% of drivers had mild and 43. 1% had moderate upper limb disability. The results of multiple regression model with a coefficient of determination of 0. 207 showed that the WBV in the presence of other predictor variables had a significant effect on DASH score (p<0. 05). Conclusion: In mining truck drivers, WBV exposure was higher and HAV exposure was lower than the national exposure limits. The results confirmed that WBV caused by mining trucks is the most important risk factor affecting the level of drivers' disability.

Loading equipment is one of the most essential equipment in open-pit mining operations. Any failure of all or some of these equipment leads to a decrease in the production and profitability of the mine. Trucks are one of the well-known machines applied for mineral transportation. The occurrence of any kind of failure in trucks leads to the stop of the loading operation and, finally the complete stop of the mining operation. Knowing the operating conditions of the mineral transport unit is one of the critical parameters to prevent unwanted stops and accordingly improve the operational performance of the equipment. Therefore, it is necessary to check the reliability and maintainability of loading machines to provide a maintenance and repair program and control the productivity of mineral transportation operations. In this paper, the reliability of seven trucks in Sungun Copper Mine, Iran, was evaluated and discussed. To achieve this, the statistical approach was used to obtain the best reliability function, and then the reliability-based preventive maintenance scheduling was proposed. The results of this paper showed that the reliability of the fleet of mining trucks decreased to 80% in 47 hours and reached zero after about 300 hours. The results of this study are helpful for mine managers and contractors to have a safe and reliable mineral transportation system.

Background: While cyclists and pedestrians are known to be at significant risk for severe injuries when exposed to road traffic accidents (RTA) involving trucks, little is known about RTA injury risk for truck drivers. Objectives: The aim of this study was to analyze the injury severity in truck drivers following RTAs. Patients and Methods: Our local accident research unit prospectively documented 43000 RTAs involving 582 trucks between 2000 and 2011. Injury severity, including the abbreviated injury scale (AIS) and the maximum abbreviated injury scale (MAIS) were analyzed. Technical parameters (e. g. delta-v, direction of impact), the location of accident, and its dependency on the road type were also taken into consideration. Results: Thirteen percent (77/582) of truck drivers were injured. Extremities were found to be at highest risk of injury with the lower extremities (36x) being injured most severely (10x: AIS 2 and 3). Death occurred only after collisions with other trucks, and severity of injuries increased with an increased speed limit. The maximum abbreviated injury scale was higher in the crash opponents (56x MAIS 3) compared to the truck drivers (8x MAIS 3). Overall, 82% of the crash opponents were injured. Conclusions: The safety of truck drivers is assured by their vehicles, the consequence being that the risk of becoming injured is likely to be low. However, the legs especially are at high risk for severe injuries during RTAs. This probability increases in the instance of a collision with another truck. Nevertheless, in RTAs involving trucks and regular passenger vehicles, the other party is in higher risk of injury.