Theoretical And Empirical Research On Maintenance Decision Of Starch Production System Based On Reliability Prediction

The equipments of modern manufacturing system have a series of features such asmaximized, complicated, automated, precision, multi-function, high-speed. Themaintenance of equipment of manufacturing system has great important effect on themanufacturing cost and production run of companies, which is the key factor of thecompetitive abilities and economic benefit of production companies. It is increasinglyimportant to explore and research on the rules of reliability of manufacturing system, toestablish effective equipment management strategies and to improve the reliability andavailability of equipment. Based on starch production line as the research object, theoreticaland empirical research on maintenance decision of starch production system based onreliability prediction are studied in this paper. The main contents of this paper are asfollows:(1) The actual preventive maintenance mostly belongs to imperfect maintenance, which cannot make the equipments as good as new. With the increase of maintenance number andequipment ages, the reliability of equipments declines increasingly. Aiming at the abovefeature, the optimizing models of preventive maintenance strategies of single equipment areset up by integrating the age reduction factor and the failure rate increase factor. On thisbasis, respectively by equipment reliability and maximum availability as constraintconditions to build up a single goal maintenance strategy model. Furthermore,it have certaininnovation and practical, to build up more flexible multi-objective dynamic preventivemaintenance model. With the three models can be obtain the optimal time interval andfrequency of equipment preventive maintenance. With maintenance data from the enterpriseactual production to verify three models. The results shows that these strategie models cancan satisfy the demand of enterprise decision. In these models, multi-objective dynamicmaintenance model is more flexible and effective. These models can afford effective supporton the preventive maintenance decisions of the equipment in production companiesTherefore, this model has a certain practical values.(2) The system reliability prediction is one of the important contents of the study of thereliability change rule. It has an important guiding significance to equipment maintenancedecision that to grasp the system reliability level. Based on the reliability prediction mathematical model, to build up reliability model for the starch processing workshoppurification section production line of the Cofco Biochemical Energy (XXX) Co., LTD.When modeling the purification section be regarded as a series system by multipleequipment, according to the series system rules and characteristics, its reliability simulationbe performed by the system reliability simulation software-BlockSim. The simulationresults show that the whole system reliability level is decreasing with production timeincreases; the biggest influence on the system reliability of equipment is electronic scale, ifwe want to improve system reliability, must first consider improving the reliability of theelectronic scale. Finally, the preventive maintenance condition system average availabilitychanging law be simulated, the simulation results show that the preventive maintenanceinterval size has great influence on the system average availability, when the interval islesser, the system availability level is higher, otherwise, the system availability level down.(3) Spare parts is the material base of the equipment maintenancet. Scientific spare partsmanagement is one of the core content to improve the equipment management efficiency, toensure that equipment reliability. This paper to determine maintenance spare partsconsumption of starch production system as the goal,to study the problem of spare partsconsumption prediction. First, the basic concepts and methods to determine the spare partsconsumption standard be introduced. At the same time, all kinds of spare parts consumptionforecast model and method be introduced. Finally, using the secondary moving averagemethod, three exponential smoothing method, index curve trend method, ARMA processmethod to the consumption of bearing6312to build simulation close, with tracking signaljudgment fitting, results show that three exponential smoothing method, index curve trendmethod, the ARMA model process method is reasonable, and TS=1.27is minimum in theARMA model. The precision of the ARMA process method is the highest, so choose themethod to forecast the consumption of bearing6321. The predicted results show that we getpredicted values is very close the original observed value of the sample by using ARMAmodel, its accuracy accord with the requirements of the enterprise. Thus it is effective thatto prediction spare parts monthly consumption in ARMA processes. ARMA model formaterial requirements is simple, need only a variable of historical data, and has a strictmathematical guarantee.It has obvious advantages in short-term prediction. This method canbe used to predicted spare parts consumption in enterprise equipment management.(4) Based on the theoretical research, this paper development the equipment maintenanceand spare parts management system for the equipment in the starch production line.By thissystem, the enterprise can timely and accurate grasp of use and maintenance condition of all equipment, spare parts, reducing the equipment maintenance cost, improving equipmentreliability, realizing various kinds of real-time information management and monitoring ofequipment failure and maintenance, etc. The development system is the special system forthe Cofco Biochemical Energy (XXX) Co., LTD. Tthrough the establishment of enterpriseequipment maintenance and spare parts management platform, the enterprise be able totimely collect, monitoring, analysis and processing equipment, spare parts, maintenancecrew, maintenance activities and equipment maintenance closely related to all aspects of thedata. The system adopts B/S framework, the database for Oracle database, a three layer datastructure management, base development using Asp.net technology. Through the developedsystem, can collect to complete the running state of the equipment information, accumulateequipment maintenance data, to strengthen equipment management, to prevent theoccurrence of fault, keep equipment efficiency, safe operation, and has important theoreticalsignificance and practical value. At the same time, using this system can effectively controlequipment maintenance activities, monitoring spare parts inventory, make the enterprisemanagement can real-time acquisition equipment maintenance information, spare partsinventory information for the production decision to provide the reference.The innovation points in this paper are as follows:(1) With the age reduction factor and the failure rate increase factor to establish the mixedfault evolution rule model,it conforms to the actual equipment recession trend. Respectivelyto construct the reliability constraints and equipment maximum availability constraints forsingle objective preventive maintenance strategy model, at the same time, multi-objectivedynamic preventive maintenance strategy model is established based on a single targetpreventive maintenance strategy model. It more can meet the requirements of the equipmentreliability, to provides powerful support for equipment maintenance decision.(2) Applying the reliability block diagram method to simplify production line system, at thesame time, to simulate reliability of the production system and system availability underdifferent preventive maintenance.(3) The utilization many kinds of mathematical model to forecast the spare partsconsumption, through the contrast analysis, find the most suitable forecast method andmodel for the Cofco Biochemical Energy (XXX) Co., LTD.