scholarly journals Coordinated optimization of production scheduling and maintenance activities with machine reliability deterioration

2021 ◽  
Vol 0 (0) ◽  
pp. 0
Author(s):  
Chaoming Hu ◽  
Xiaofei Qian ◽  
Shaojun Lu ◽  
Xinbao Liu ◽  
Panos M Pardalos
Keyword(s):  
Production Scheduling ◽  
Optimization Problem ◽  
Maintenance Cost ◽  
Grey Wolf Optimizer ◽  
Computational Stability ◽  
Processing Sequence ◽  
Production Stage ◽  
Machine Failure ◽  
Machine Reliability ◽  
Coordinated Optimization

<p style='text-indent:20px;'>In this paper, we investigate a coordinated optimization problem of production and maintenance where the machine reliability decreases with the use of the machine. Lower reliability means the machine is more likely to fail during the production stage. In the event of a machine failure, corrective maintenance (CM) of the machine is required, and the CM of the machine will cause a certain cost. Preventive maintenance (PM) can improve machine reliability and reduce machine failures during the production stage, but it will also cause a certain cost. To minimize the total maintenance cost, we must determine an appropriate PM plan to balance these two types of maintenance. In addition, the tardiness cost of jobs is also considered, which is affected not only by the processing sequence of jobs but also by the PM decision. The objective is to find the optimal job processing sequence and the optimal PM plan to minimize the total expected cost. To solve the proposed problem, an improved grey wolf optimizer (IGWO) algorithm is proposed. Experimental results show that the IGWO algorithm outperforms GA, VNS, TS, and standard GWO in optimization and computational stability.</p>

scholarly journals Multi-Objective Sizing Optimization of Hybrid Renewable Energy Microgrid in a Stand-Alone Marine Context

Electronics ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 174
Author(s):  
Wenqiang Zhu ◽  
Jiang Guo ◽  
Guo Zhao
Keyword(s):  
Renewable Energy ◽  
Optimization Problem ◽  
System Optimization ◽  
Economic Benefits ◽  
Grey Wolf Optimizer ◽  
Grey Wolf ◽  
Energy Management Strategy ◽  
Sizing Optimization ◽  
Multi Objective ◽  
Hybrid Renewable Energy

Islands are the main platforms for exploration and utilization of marine resources. In this paper, an island hybrid renewable energy microgrid devoted to a stand-alone marine application is established. The specific microgrid is composed of wind turbines, tidal current turbines, and battery storage systems considering the climate resources and precious land resources. A multi-objective sizing optimization method is proposed comprehensively considering the economy, reliability and energy utilization indexes. Three optimization objectives are presented: minimizing the Loss of Power Supply Probability, the Cost of Energy and the Dump Energy Probability. An improved multi-objective grey wolf optimizer based on Halton sequence and social motivation strategy (HSMGWO) is proposed to solve the proposed sizing optimization problem. MATLAB software is utilized to program and simulate the optimization problem of the hybrid energy system. Optimization results confirm that the proposed method and improved algorithm are feasible to optimally size the system, and the energy management strategy effectively matches the requirements of system operation. The proposed HSMGWO shows better convergence and coverage than standard multi-objective grey wolf optimizer (MOGWO) and multi-objective particle swarm optimization (MOPSO) in solving multi-objective sizing problems. Furthermore, the annual operation of the system is simulated, the power generation and economic benefits of each component are analyzed, as well as the sensitivity.

scholarly journals Predictive Maintenance of Cash Dispenser Using a Cognitive Prioritization Model

2021 ◽  
Vol 15 (1) ◽  
pp. 156-161
Author(s):  
Archana Dixit ◽  
Amol B. Mahamun
Keyword(s):  
Machine Learning ◽  
Environmental Factors ◽  
Business Processes ◽  
Time Window ◽  
Service Planning ◽  
Maintenance Cost ◽  
Business Impact ◽  
Revenue Growth ◽  
Machine Failure ◽  
Emerging Patterns

In this technical paper, we address the issue of predicting cash dispenser (addressed as ‘Device’ henceforth) failure by harnessing the power of humungous data from service history, logs, metrics, transactions, and plausible environmental factors. This study helps increase device availability, enhanced customer experience, manage risk &amp; compliance and revenue growth. It also helps reduce maintenance cost, travel cost, labour cost, downtime, repair duration and increase meantime between failures (MTBF) of individual components. This study uses a cognitive prioritization model which entails the following at its core; a) Machine Learning engineered features with highest influence on machine failure, b) Observation Windows, Transition Windows and Prediction Windows to accommodate various business processes and service planning delivery windows, and c) A forward-looking evaluation of emerging patterns to determine failure prediction score that is prioritized by business impact, for a predefined time window in the future. The model not only predicts failure score for the devices to be serviced, but it also reduces the service miss impact for the prediction windows.

scholarly journals A meta-heuristic algorithm for integrated optimization of dynamic resource allocation planning and production scheduling in parallel machine system

2019 ◽  
Vol 11 (12) ◽  
pp. 168781401989834
Author(s):  
Na Wang ◽  
Yaping Fu ◽  
Hongfeng Wang
Keyword(s):  
Resource Allocation ◽  
Heuristic Algorithm ◽  
Production Scheduling ◽  
Optimization Problem ◽  
Manufacturing System ◽  
Parallel Machine ◽  
Dynamic Resource Allocation ◽  
Integration Problem ◽  
Advanced Information Technology ◽  
Dynamic Resource

With the wide application of advanced information technology and intelligent equipment in the manufacturing system, the decisions of design and operation have become more interdependent and their integration optimization has gained great concerns from the community of operational research recently. This article investigates an optimization problem of integrating dynamic resource allocation and production schedule in a parallel machine environment. A meta-heuristic algorithm, in which heuristic-based partition, genetic-based sampling, promising index calculation, and backtracking strategies are employed, is proposed for solving the investigated integration problem in order to minimize the makespan of the manufacturing system. The experimental results on a set of random-generated test instances indicate that the presented model is effective and the proposed algorithm exhibits the satisfactory performance that outperforms two state-of-the-art algorithms from literature.

scholarly journals Analog tachometer as an indicator motorcycle machine wearing based on moving coil

2018 ◽  
Vol 43 ◽  
pp. 01004
Author(s):  
Dhanis Woro Fittrin Selo Nur Giyatno ◽  
Tommy Richard Orlando ◽  
Nining Supriatin
Keyword(s):  
Control Unit ◽  
Electrical Energy ◽  
Electrical Current ◽  
Maintenance Cost ◽  
Current Sensing ◽  
Variable Resistor ◽  
Rotary Machine ◽  
System A ◽  
Machine Reliability ◽  
Electronic Instrumentation

As an increasing highly mobility and high traffic, the necessary of motorcycle is highly increasing. The condition makes user ride motorcycle with highly speed in highly frequency. Then, these conditions make motorcycle machine reliability is highly decreasing. Finally, it made machine is run to damage and maintenance cost to be high. Analog tachometer is an electronic instrumentation that proposed to solve these problems. Actually, instrumentation system of tachometer is an electromechanical system. A wire in a control unit is embedded into shaft of crank. Then, magnet in control unit will convert rotary machine energy into electrical energy with d’Arsonval meter. Current sensor and small variable resistor are the kind of sensor that are used in tachometer. Small variable resistor is used for tuning and recalibration. Utilization small variable resistor in tachometer circuit is make calibration and recalibration current sensing of electrical current that rectified by diode. Tachometer for counting rotation per minute (RPM) motorcycle machine is built up. The tachometer has capability to count RPM motorcycle machine 1,000 – 13.000 RPM. The range is reliable as an indicator for user to minimize motorcycle machine wearing.

A FMS Dynamic Scheduling Optimization Strategy and Simulation Research

2013 ◽  
Vol 389 ◽  
pp. 692-697
Author(s):  
Ji Zhuang Hui ◽  
Xiang Ding ◽  
Kai Gao
Keyword(s):  
Production Scheduling ◽  
Dynamic Scheduling ◽  
Scheduling Problems ◽  
Optimization Strategy ◽  
Scheduling Optimization ◽  
Simulation Research ◽  
Scheduling Strategy ◽  
Machine Failure ◽  
Rolling Window ◽  
Scheduling Optimization Algorithm

This paper studied the FMS dynamic scheduling problem which was based on Petri net FMS static scheduling optimization algorithm, which in accorder to solve the FMS actual production scheduling problems. A rolling window dynamic re-scheduling strategy was proposed which based on event driven and cycle driven. Then take the emergency machine failure often appearing in the actual workshop for example, this scheduling strategy was analyzed and applied to dynamic simulation and finally the effectiveness of the dynamic scheduling strategy was verified.

scholarly journals Swarm optimization approach to non-stationary physical eld survey problem using a group of autonomous underwater vehicles

2020 ◽  
Author(s):  
A. Tolstikhin ◽  
I. Bychkov
Keyword(s):  
Optimization Problem ◽  
Autonomous Underwater Vehicles ◽  
Underwater Vehicles ◽  
Grey Wolf Optimizer ◽  
Optimization Approach ◽  
Vast Number ◽  
Swarm Algorithms ◽  
Whale Optimization ◽  
Low Dimensional ◽  
The Given

The paper considers the problem of searching for the source of a non-stationary physical eld. We assume that the use of swarm algorithms may be applicable in this case. A hybrid of the Whale Optimization Algorithm and Grey Wolf Optimizer is proposed in this paper. The algorithm has several advantages over its origins: a more precise solution of the optimization problem for low-dimensional functions and a higher convergence rate of the first iterations. Two modications were made to adapt the algorithm to the requirements of the problem. The proposed algorithm is used as a basis for a control strategy for a group of autonomous underwater vehicles. As a result, in the vast number of cases, the group can find the source within the given number of search iterations.

scholarly journals Forecasting Machine Failure Using DMG and Weibull Analysis in an Automotive Industry: A Case Study

2021 ◽  
Vol 40 (2) ◽  
pp. 435-442
Author(s):  
Kamran Shah ◽  
Hassan Khurshid ◽  
Izhar Ul Haq ◽  
Shaukat Ali Shah ◽  
Zeeshan Ali
Keyword(s):  
Decision Making ◽  
Manufacturing Industry ◽  
Management Strategies ◽  
Fixed Time ◽  
Maintenance Management ◽  
Maintenance Cost ◽  
Weibull Analysis ◽  
Effect Analysis ◽  
Machine Failure ◽  
Computerized Maintenance Management System

In manufacturing or production setup, maintenance cost is one of the major portions of overall operating expenditure. It can vary between 15 to 60 percentage of overall cost for various industries including food related industries, iron, steel and other heavy industries. Such a high cost directly impacts manufacturing setup, profitability and sustainability in long run. In most of the industries, ineffective maintenance management can result in loss of capital and inefficient human resource deployment. This in turn affects the plants’ ability to manufacture quality products that are competitive in the market. Various maintenance management strategies including Operate to Failure (OTF), Design Out Maintenance (DOM), Skill Level Upgrade (SLU), ConditionBased Monitoring (CBM) and Fixed Time Maintenance (FTM) are used in industries for maximizing productivity. In recent years, Computerized Maintenance Management System (CMMS) has become an integral part of most of the industries so its importance and characteristics cannot be understated. While CMMS cannot live standalone, it requires some decision-making techniques to be equipped with. These techniques range from Failure Mode and Effect Analysis (FMEA) to Decision Making Grid (DMG). In this paper, concept of DMG has been applied to an automotive parts Manufacturing Industry in conjunction with Weibull analysis. Parallels are drawn between the results of DMG and Weibull analysis.

scholarly journals Applying Quantum Optimization Algorithms for Linear Programming

2017 ◽  
Author(s):  
Mert Side ◽  
Volkan Erol
Keyword(s):  
Resource Allocation ◽  
Linear Programming ◽  
Production Scheduling ◽  
Optimization Problem ◽  
Optimization Problems ◽  
Quantum Algorithms ◽  
Quantum Algorithm ◽  
Quantum Computers ◽  
Quantum Optimization ◽  
Special Case

Quantum computers are machines that are designed to use quantum mechanics in order to improve upon classical computers by running quantum algorithms. One of the main applications of quantum computing is solving optimization problems. For addressing optimization problems we can use linear programming. Linear programming is a method to obtain the best possible outcome in a special case of mathematical programming. Application areas of this problem consist of resource allocation, production scheduling, parameter estimation, etc. In our study, we looked at the duality of resource allocation problems. First, we chose a real world optimization problem and looked at its solution with linear programming. Then, we restudied this problem with a quantum algorithm in order to understand whether if there is a speedup of the solution. The improvement in computation is analysed and some interesting results are reported.

scholarly journals Analysis of critical machine reliability in manufacturing cells

2019 ◽  
Vol 12 (1) ◽  
pp. 70 ◽  
Author(s):  
Manocher Djassemi ◽  
Hamid Seifoddini
Keyword(s):  
Simulation Model ◽  
Flow Line ◽  
Discrete Event ◽  
Production Capacity ◽  
Business Environment ◽  
Manufacturing Cells ◽  
Machine Failure ◽  
Machine Reliability ◽  
Critical Machine ◽  
Critical Machines

Purpose: In an increasingly competitive business environment, machine reliability problem merits special attention in operations of  manufacturing cells. This is mainly due to flow line nature of the cellular layout, interdependency of downstream and upstream of machines related to each other. This study investigates the effect of critical machine reliability improvement  on production capacity and throughput time in manufacturing cells.  Design/methodology/approach: A discrete-event simulation model was developed to investigate the effectiveness of a reliability plan focusing on the most critical production machines in improving the performance level as an alternative to increasing the reliability of all machines. Four machine criticality policies are examined in the simulation experiments.Findings: The results of this experimental study indicated that an improvement of reliability of a limited number of machines leads to an increase in overall production capacity and speed in cellular manufacturing operations. A reliability plan, that focuses on a set of critical machines, potentially offers a more economical alternative to increasing the reliability of all machines in such facility.Research limitations/implications: The results demonstrate that to achieve higher production capacity and shorter throughput times, managers should consider directing more resources to increase the reliability of critical machines, particularly, those with shorter mean time to failure and higher utilization.Originality/value: The designed simulation model is unique in representing the dynamics of a real world manufacturing cell environment by encoding operational functions such as machine failure, maintenance resource allocation, material flow, job sequencing and scheduling. A new machine availability metric is defined as well. 

scholarly journals The Method of Production Scheduling with Uncertainties Using the Ants Colony Optimisation

2020 ◽  
Vol 11 (1) ◽  
pp. 171
Author(s):  
Iwona Paprocka ◽  
Damian Krenczyk ◽  
Anna Burduk
Keyword(s):  
Numerical Simulations ◽  
Production System ◽  
Production Scheduling ◽  
Flow Shop ◽  
Ant Colony Optimisation ◽  
Maintenance Costs ◽  
Machine Failure ◽  
Scheduling Method ◽  
Method Of Production ◽  
Flow Shop Systems

Production and maintenance tasks apply for access to the same resources. Maintenance-related machine downtime reduces productivity, but the costs incurred due to unplanned machine failures often outweigh the costs associated with predictive maintenance. Costs incurred due to unplanned machine failure include corrective maintenance, reworks, delays in deliveries, breaks in the work of employees and machines. Therefore, scheduling of production and maintenance tasks should be considered jointly. The problem of generating a predictive schedule with given constrains is considered. The objective of the paper is to develop a scheduling method that reflects the operation of the production system and nature of disturbances. The original value of the paper is the development of the method of a basic schedule generation with the application of the Ant Colony Optimisation. A predictive schedule is built by planning the technical inspection of the machine at time of the predicted failure-free time. The numerical simulations are performed for job/flow shop systems.

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