Content uploaded by Saeid R Dindarloo
Author content
All content in this area was uploaded by Saeid R Dindarloo on Feb 16, 2017
Content may be subject to copyright.
A preview of the PDF is not available
Mining Truck-Related Accidents:Multi-Objective Economic Optimization of Safety
Abstract and Figures
Off-road-truck-related accidents are a major cause of considerable losses in the US surface mining industry. Though the rates of fatalities, permanent disabilities and other injuries have shown decreasing trends in the past decade, the associated lost lives and working days are far from a “zero work place accident policy” in this industry. After identification of the root cause(s) of off-road truck related accidents, the major task is to decide on the implementation of appropriate safety measures. In cases that there are several alternatives, an optimal decision should be taken in order to choose the most effective alternative(s) which incur minimum costs while achieving maximum improvements. The three major objectives are defined, in this study, as (i) maximization of loss prevention, (ii) minimization of costs, and (iii) maximization of reliability of safety measures. A multi-objective three-function-two-variable mathematical framework for optimization of the decision is proposed. The framework is examined in a generic mining situation to demonstrate its applicability. The genetic algorithm method was used to solve the multi-objective decision problem. The results identified the most effective safety measures and the optimal time interval that each one should be employed to achieve the best results.
Figures - uploaded by Saeid R Dindarloo
Author content
All figure content in this area was uploaded by Saeid R Dindarloo
Content may be subject to copyright.
ResearchGate has not been able to resolve any citations for this publication.
In recent years, the greatest safety threat to military personnel has been from underbody vehicle blast events, but other major threats exist against fuel convoys and due to rollover events. Ground vehicle designers make choices that affect one or more of these risk areas, including the weight and structural design of the vehicle underbody, as well as the design of seating systems that cushion the occupants from the rapid accelerations caused by blast loading. This study uses mathematical and computational tools to evaluate underbody blast, fuel convoy, and rollover safety criteria, and the models are combined into a multi-objective design optimization formulation that minimizes personnel casualties. The models and framework are highlighted and described in detail, and preliminary optimization results are presented under various conditions. The multi-objective behavior of the design problem is explored through weighted-objective Pareto frontiers, and the utility of the model in real-world situations is discussed.
The problems of limited financial resources and water scarcity in urban areas of developing countries are of concern to water managers following growing demand-supply imbalance. As a result, an intermittent supply is widely adopted as a measure for controlling water demand among consumers. However, ensuring equitable water distribution at low cost in intermittent water supply systems becomes a challenge. Most intermittent water supply systems fail to achieve both objectives and how to improve equity remains a complex task for water managers. There is little research in this area and therefore a need to develop more appropriate optimisation techniques that recognise this unique feature of intermittent systems in developing countries. The paper proposes a simple multiobjective optimisation model to measure and improve equity and minimise cost in intermittent distribution networks, under water scarcity condition. A simple network is subjected to intermittent supply to demonstrate the model, in which both locations and capacities of source tanks/reservoirs are subject to optimisation. A simulation model is used to model intermittent systems as pressuredependent through the use of consumer storage tanks. The paper reveals that equity under intermittent supply conditions is measurable and can be improved through optimal location and sizing of elevated source reservoirs.
The authors present a procedure for allocating resources for implementing safety improvement alternatives at urban intersections over a multi-year planning horizon. The procedure, based upon optimization techniques, attempts to maximize benefits-measured in dollars saved by reducing crashes of different severity categories, subject to budgetary and other constraints. It is presented in two parts (1) a Base case including the objective function and a set of mandatory constraints, and (2) additional policy constraints / special features that can be separately incorporated to the Base case. Demonstration of the procedure is presented on intersections in the Detroit metropolitan region, where economic losses resulting from traffic crashes at intersections are estimated to exceed $4 billion annually. The proposed model can allocate resources for safety improvement alternatives over a planning horizon, given a number of independent locations and a number of mutually exclusive alternatives at each location. The policy constraints provide the analyst the flexibility of adding equity, urgency, and other features to the Base case. Integer programming technique is applied to solve the demonstration problem.
The main objective of this review was to build upon a previous study on the root causes of truck-related fatalities in surface coal mining operations in West Virginia, and to develop intervention strategies to eliminate these fatalities. This review considers a two-pronged approach to accident prevention: one that is fundamental and traditional (safety regulations, training and education, and engineering of the work environment); and one that is innovative and creative (e.g., applying technological advances to better control and eliminate the root causes of accidents). Suggestions for improving current training and education system are proposed, and recommendations are provided on improving the safety of mine working conditions, specifically safety conditions on haul roads, dump sites, and loading areas. We also discuss various currently available technologies that can help prevent haul truck-related fatal accidents. The results of this review should be used by mine personnel to help create safer working conditions and decrease truck-related fatalities in surface coal mining.
Recently increasing attention has been given to a hydrogen infrastructure (HI) including producing, transporting, and delivering H-2, the next generation alternative renewable energy source to users. This paper is concerned with designing the HI considering multiple perspectives of economic cost efficiency, safety and low CO2 emission simultaneously. An optimization modeling approach is thus proposed to address such multiple objectives of cost efficiency of H-2 supply, safety guarantee and cost efficiency of CO2 mitigation in the HI design. The proposed model employs fuzzy multiple objective programming to compute a compromising solution among multiple objectives. A case study of the future HI in Korea is presented to demonstrate the applicability of the proposed model with some comments. The proposed modeling work can be further utilized for developing systematic decision-making tools for policy makers to determine investment strategies for developing HIs.
Consider the following basic model in economic safety analysis: a firm is willing to invest an amount x in safety measures to avoid an accident A which, in the case of occurrence, leads to a loss of size L. The probability of an accident is a function of x. The optimal value of x is determined by minimizing the expected costs. In the present paper we study this model (and an extended version of it) in an applied risk/safety management setting, which allows for imprecise probabilities for the accident probabilities. The imprecision reflects the fact that the knowledge basis for assigning the probabilities is poor and based on many assumptions, and also that there are different knowledge bases among relevant experts and stakeholders. The purpose of the paper is to present and discuss a set-up for the precise formulation of this type of problems and show how they can be solved. We demonstrate in the paper how an optimal investment level x can be determined under different sets of situations and conditions, including one where a tolerability limit is defined for the accident probability. The main conclusion of the paper is that the robust optimization methods could in practice provide useful decision support but should be supplemented with sensitivity analyses showing the optimal investment levels for various parameter values followed by qualitative analyses providing arguments supporting the different parameter values.
A general optimization model is proposed to determine the optimal plant layout with the simultaneous consideration of economic and safety aspects. An important characteristic of the proposed optimization model is that it allows the relocation of some of the existing units to reduce the risks associated with current locations. The formulation also allows the addition of new units. A multiobjective mixed-integer linear programming model (MO-MILP) is developed to determine the optimal location of new and existing units while accounting for cost and risk. The proposed model is analyzed through a case study for a hexane distillation process showing the advantages of considering the possibility of relocating units originally installed following exclusively heuristic approaches and economic criteria.
Trucks are the primary means of haulage in surface coal, metal, and nonmetal mining operations. The number of fatal accidents involving trucks is higher when compared to all other mining equipment. Mine Safety and Health Administration (MSHA) reports that 137 fatalities were haul truck-related in the United States between 1995 and 2011. A total of 12 accidents, including 13 fatalities, were recorded in surface coal mining operations in West Virginia (WV) during this period. The objective of this study was to better understand the root causes of accidents in WV. The Fault Tree Analysis (FTA) technique was used to systematically analyze these accidents. Results of the study indicate that inadequate or improper pre-operational check and poor maintenance of trucks were the two most common root causes of these accidents. A total of eight accidents occurred on haul roads, while 10 accidents occurred while the trucks were moving forward. The two most violated provisions of Code of Federal Regulations were 30 CFR§77.404 – Machinery and equipment; operation and maintenance (six times), and 30 CFR§77.1606 – Loading and haulage equipment; inspection and maintenance (five times).
The multiobjective ant colony system (ACS) meta-heuristic has been developed to provide solutions for the reliability optimization problem of series-parallel systems. This type of problems involves selection of components with multiple choices and redundancy levels that produce maximum benefits, and is subject to the cost and weight constraints at the system level. These are very common and realistic problems encountered in conceptual design of many engineering systems. It is becoming increasingly important to develop efficient solutions to these problems because many mechanical and electrical systems are becoming more complex, even as development schedules get shorter and reliability requirements become very stringent. The multiobjective ACS algorithm offers distinct advantages to these problems compared with alternative optimization methods, and can be applied to a more diverse problem domain with respect to the type or size of the problems. Through the combination of probabilistic search, multiobjective formulation of local moves and the dynamic penalty method, the multiobjective ACSRAP, allows us to obtain an optimal design solution very frequently and more quickly than with some other heuristic approaches. The proposed algorithm was successfully applied to an engineering design problem of gearbox with multiple stages.