چكيده لاتين :
Nowadays, one of the basic foundations in the industry and production is undoubtedly equipment and machinery. On the other hand, increasing productivity will not be possible without increasing the usability and utilization time of equipment and machinery. Today, with human progress in various fields of knowledge, the needs of industries have changed, and the concepts of reliability and availability have found a special place in industrial systems. Increasing the level of reliability and availability of their equipment is one of the goals of industrial organizations. In any modern society, engineers and technical managers are responsible for planning, designing, building, and operating from the simplest product to the most complex systems. The failure of products and systems disrupts various levels and can even be considered a serious threat to society and the environment.
For this reason, consumers and society at large expect products and systems to be reliable, trustworthy, and secure. Therefore, instead of focusing on reducing costs, we should focus on increasing reliability. The cement industry is now increasingly competitive. Designers and manufacturers of production equipment to increase the production capacity of machinery and compete with other manufacturers of production machinery have turned to the design of complex and low-energy machinery to reduce production costs. With increasing dependence on complex and low-consumption machinery, the issue of the ability to ensure the performance of industrial machinery becomes more significant. At this time, to control and manage equipment repair costs and also to find ways to increase their useful life and prevent production shutdowns due to equipment failure and eliminate its adverse effects, the study of factors affecting the reliability of equipment seems useful.
Reliability is particularly significant in continuous manufacturing systems where the failure of some components will cause the entire system to malfunction and cause the total system to shut down. Therefore, it is necessary to identify all the factors affecting the system reliability to prevent many problems of system failure. Reliability assessment is very important in industries with continuous processes such as the cement industry, in which every hour of downtime in the production process causes a lot of damage. To increase reliability, while emphasizing the correction of accidental breakdowns and unexpected equipment malfunctions, so far with the proper use of science, statistics and probabilities and operational research, simulation, engineering economics Queue theory, techniques for different modes of devices and equipment, have been developed. Studies on improving reliability are extensive. Much of the research in this area has been on allocating redundancy or increasing reliability based on maintenance strategies. In redundancy allocation problems, mathematical modeling is used to maximize reliability.
Usually, the models used for redundancy allocation and reliability-based maintenance focus on only a small number of variables, and a large number of important variables, including the role of equipment operator and human reliability, are neglected. Therefore, this article tries to create a model that includes all the factors affecting the reliability of cement equipment. Given that the relationship between variables and factors affecting reliability has a lot of dynamics and feedback, system dynamics is a good tool for analyzing factors affecting reliability. System dynamics is used as a method to study the dynamic behavior of the system by emphasizing the relationships between the components of the system. By simulating and analyzing system behavior using various hypotheses, this method provides feedback to policymakers on the impact of policies so that they can make policies efficiently and effectively. Mathematical models are flawed because they do not take into account feedback loops, while dynamic systems solve this problem and are more effective when making decisions. In other words, in dynamic models, paying attention to the time dimension and the feedback between the model variables and paying attention to the multiple relationships between the variables, takes the traditional models out of static state and their ability to predict. In this way, it is possible to evaluate and control the reliability of the equipment and fill the existing vacuum with a systemic approach. In this research, an attempt has been made to identify the factors affecting the reliability of Ghaen Cement Factory equipment. For this purpose, first, the behavior of variables related to a period and affecting the reliability of equipment was analyzed and evaluated simultaneously with obtaining an expert opinion and studying identification sources. After identifying the problem variables, the dynamic nature of the problem was presented in the form of feedback loops by identifying the relationships of the variables. After identifying the subsystems, feedback was generated in each subsystem. After identifying the key variables and finding the causes of these variables, a causal-circular diagram was drawn. Putting together dynamic hypotheses, the general structure of the dynamic model of the problem was introduced as follows. These two subsystems are connected by the variable of staff training and total cost. After identifying the factors and variables as well as the formation of cause and effect relationships between them in the form of a dynamic hypothesis, the accumulation and flow diagrams were drawn. Flowcharts are useful for representing physical or information flows in a system dynamics model. State variables are represented as rectangles that represent the accumulated currents at that surface. In other words, state variables aggregate the results of actions within a system.
Accumulations in this model (mode variables) include total reliability, net-based reliability, equipment design reliability, humanity reliability, profit, staff skills, broken equipment, discovered defects, quality improvement program, again Labor, waste, and product price. The most important variables of reliability improvement rate include failure rate, repair rate, defect correction rate, defect detection rate, humanity capacity increase rate, human cognitive error rate, employee skill increase rate, staff capacity reduction rate, the rate of correction of defects, the rate of repairs performed. By completing the model simulation and also entering the relationship between the variables in the Vensim software, the model outputs were obtained by performing the simulation. This simulation has been performed over a five-year time horizon.
It can be seen that the quality of the process maintenance system has increased from 25 units at the beginning of the simulation period to about 180 units at the end of the period. Staff skills, as one of the effective factors in improving a maintenance system, have also grown during the simulation period. So that from about 600 units at the beginning of the period to about 2260 units at the end of the period. The failure rate, as an exponential distribution function, has been decreasing, from about 0.9 at the beginning of the first month to about zero at the end of the simulation period. The number of equipment and machinery failures has been linear and decreasing. This rate has risen from about 60 cars at the beginning of the first month to about zero cars at the end of the simulation period.
In this study, the data of the last three years have been used to examine the validity of the designed model in more detail. Production and sales volumes of the product are in tons.
As can be seen, the simulated results of the variables of production, sales, and number of customers are very close to the actual results. This indicates that the behavior of the studied variables is well simulated. Therefore, due to the small difference between real and simulated data, the validity of the model can be understood. This study states that if the variables affecting reliability are changed, such as the level of staff training, resources allocated to preventive maintenance, the quality of maintenance and repairs, etc., reliability will increase significantly. At the end of the simulation period, the total reliability has reached about 700,000, the repair and maintenance reliability has reached about 600,000, and the humanity reliability has reached 3500 units. The model presented in this research is more complete than previous models in terms of modeling, but it can be improved by adding other subsystems and adapting to the industry. Reliability of equipment design has a great role in the performance and reliability of all equipment. In this study, the related variables are not fully identified and the model can be improved by identifying more variables. Also, by defining new variables such as comprehensive productivity notes and predictive notes, it completed the note-related subsystem. By adding more variables to the initial model, it makes the model's behavior closer to reality and managers can make better strategic decisions.
