Model of Maintenance Planning Based on Trend of Machines Failures with Two Priorities

In this article we are discussing the suggestion of planning maintenance in such situation that we have failures in database of failures and maintenance registered also according to type of failure— priority or non-priority. We are assuming that maintenance must be mainly oriented on avoiding major failures of machines. The effect of maintenance manifests with delay and is dependent on development of failures. We express this problem as linear programming task that is solvable with Solver-extension of application Excel. We demonstrate the suggested solution on example of failures of machines between years 2010 and 2012.

Considering deterioration propagation in transportation infrastructure maintenance planning

Civil infrastructure system maintenance planning is to determine which facility should be repaired,when and how maintenance should be carried out,and what treatment should be used under budget and other resource constraints.In the existing literature,various simulation and optimization models have been developed to help select the optimal maintenance plan.However,the developed models overlooked the deterioration propagation between adjacent connected facilities of the network infrastructure system.For instance,a facility receiving zero maintenance or having a failure of maintenance treatment affects not only the condition of itself,but also the deterioration rate of its neighboring facilities.This raises the call for taking the deterioration propagation into consideration when developing optimization models and capture to which extent it can affect the optimal maintenance plan.Therefore,in this paper,an infrastructure maintenance planning model considering the deterioration propagation between facilities is formulated as a mixed integer linear programming problem.A heuristic algorithm was proposed to solve the problem efficiently.Example networks were tested for the performance comparison between CPLEX and the heuristic algorithm.The proposed model performs better than models without the deterioration propagation.

Movement of Autonomous Vehicles in Work Zone Using New Pavement Marking: A New Approach

The autonomous vehicles are the future of mobility across the globe and are expected to touch the lives of every person of all ages. But this comes with certain challenges regarding safety, reliability, cost, legal framework, regulations, etc. however, of all the concern safety and reliability are of utmost importance for researchers and engineers. The current research is focused on the movement of the autonomous vehicle in the work zone. The work zone is one of the most challenging areas for the autonomous vehicle to drive from. This is because the work zones are very dynamic, and all the construction activities are specific to the site condition and cannot always be predefined. The study provides a concept of how pavement marking can be used for smooth movement through the complicated work zone. In this study, various pavement marking signs have been designed as a concept considering the standard colors and striping width being used in the Manual of Uniform Traffic control device (MUTCD). The study assumes that the movement of the autonomous vehicle will not be exclusive and that it will move with the driver driven vehicle. It is expected that autonomous vehicles will require special pavement marking and signage for smooth movement through the work zone. These pavement marking and signage will eventually become part of standard Traffic Control Plans (TCP) and Maintenance of Traffic Plans (MOT). The research aims to study the current research being done in this area and technology being used for detecting various pavement markings and signages.

Deep digital maintenance

With the emergence of Industry 4.0, mainte-nance is considered to be a specific area of action that is needed to successfully sustain a competitive advantage. For instance, predictive maintenance will be central for asset utilization, service, and after-sales in realizing Industry 4.0. Moreover, artificial intelligence （AI） is also central for Industry 4.0, and offers data-driven methods. The aim of this article is to develop a new maintenance model called deep digital maintenance （DDM）. With the support of theoretical foundations in cyber-physical systems （CPS） and maintenance, a concept for DDM is proposed. In this paper, the planning module of DDM is investigated in more detail with realistic industrial data from earlier case studies. It is expected that this planning module will enable inte- grated planning （IPL） where maintenance and production planning can be more integrated. The result of the testing shows that both the remaining useful life （RUL） and the expected profit loss indicator （PLI） of ignoring the failure can be calculated for the planning module. The article concludes that further research is needed in testing the accuracy of RUL, classifying PLI for different failure modes, and testing of other DDM modules with industrial case studies.

Establishing simulation model for optimizing efficiency of CNC machine using reliability-centered maintenance approach

The objective of this work was to enhance the product’s quality by concentrating on the machine’s optimized efficiency.In order to increase the machine’s reliability,the basis of reliability-centered maintenance approach was utilized.The purpose was to establish a planned preventive maintenance strategy to identify the machine’s critical components having a noteworthy effect on the product’s quality.The critical components were prioritized using failure mode and effect analysis(FMEA).The goal of the study was to decrease the ppm time interval for a CNC machine by simulating the projected preventive maintenance time interval.For this purpose,the simulation software ProModel 7.5 was implemented for the current preventive maintenance procedure to choose the best ppm time interval which contributed better norms.Five dissimilar optimization approaches were applied,however,the first approach yielded the prominent total system cost and the shorter ppm interval.The results of the study revealed that there was an increase of USD 1878 as a result of an increase in total system cost from USD 78,365 to USD 80,243.Preventive maintenance costs were reduced from USD 4196 to USD 2248(46%).The costs associated with good parts increased from USD 8259 to USD 8294(0.4%)and the costs associated with defective parts reduced from USD 171 to USD 3(98.25%),respectively.