Application of Fractal in Machine Downtime Control

Xuan-xuan, LI; Li, Bo; Xu, Limei; Li, Sean

doi:10.1109/icma.2007.4303687

Cited by 5 publications

(4 citation statements)

References 17 publications

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“…3.4 Implications. The consequences of machine downtime could be severe for operating plants in bottling processes as they operate in competitive environments where dissatisfied customers may take their custom elsewhere and be lost forever if their bottled products being demanded are not available (Li et al, 2007). Practically, this makes us urge general managers and maintenance engineers to undertake a complete impact assessment of their systems and procedures to permit the bottling plant in interventions that will stimulate recovery goals in situations of extreme downtime.…”

Section: Downtime Evaluation In a Factorymentioning

confidence: 99%

“…Enginarlar et al (2002) stated that machine downtime regularly results in loss of throughput in manufacturing processes. Li et al (2007) have provided general evidence regarding how a fractal-rooted approach for machine downtime pattern and accomplishment direction could be quantified. Patti et al (2008) offered an argument about the shape of protective capacity regarding unbalancing lines in situations of changes regarding unplanned machine downtime with the use of Kanban as well as drum-buffer-rope directed production systems.…”

Section: Introductionmentioning

confidence: 99%

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Maintenance downtime evaluation in a process bottling plant

Inyiama

Oke

2020

IJQRM

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PurposeDowntime is a process parameter that substantially impacts on the operating hours and results in production losses, thus motivating maintenance engineers to control process plants. Notwithstanding, the impacting nature of process equipment failure on the operating hours in bottling plants remains inadequately examined. In this paper, the cause-and-effect analysis was used to establish the root cause of the downtime problem and Pareto analysis employed to justify the greatest opportunities for improvement in reducing downtime and increasing reliability levels. Weibull analysis is then conducted on the industrial setting. Novel aspect ratios are proposed.Design/methodology/approachUsing the Weibull failure function of machines as a principal facilitator to produce failure predictions, the downtime behaviour of a process plant was modelled and tested with practical data from a bottling process plant. This research was conducted in a Nigerian process bottling plant where historical data were examined.FindingsThe analysis of the results shows the following principal outcome: First, the machines with the highest and least downtime values are 2 and 5, respectively, with correspondingly mean values of 22.83 and 4.39 h monthly. Second, the total downtime 92.05 and 142.14 h for the observed and target downtime, with a coefficient of determination of 0.5848 was recorded. Third, as month 1 was taken as the base period (target), all the machines, except M5 had accepted performance, indicating proper preventive maintenance plan execution for the bottling process plant. Availability shows a direct relationship between the failure and uptime of the machines and the downtime impacts on production. Two machines had random failure pattern and five machines exhibited a wear-out failure pattern and probably due to old age and wear of components in the machines.Originality/valueThe major contribution of the paper is the Weibull modelling in a unique application to a bottling plant to avoid current practices that use reliability software that is not easily accessible.

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Section: Downtime Evaluation In a Factorymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Maintenance downtime evaluation in a process bottling plant

Inyiama

Oke

2020

IJQRM

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“…1 Unexpected machine failures directly impact machine availability, which leads to decreased capacity, high maintenance cost, and risks to production profitability and competitiveness. 2 Generally the downtime costs of industrial production equipment are high. Failures in such machines are expensive not only because of the high repair costs involved but because of the cost of lost production.…”

Section: Introductionmentioning

confidence: 99%

Spare Parts Estimation for Machine Availability Improvement Addressing Its Reliability and Operating Environment — Case Study

Ghodrati

Ahmadi

Galar

2013

Int. J. Rel. Qual. Saf. Eng.

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Industrial operation cost analysis shows that, in general, maintenance represents a significant proportion of the overall operating costs. Therefore, the improvement of maintenance follows the final goal of any company, namely, to maximize profit. This paper studies spare parts availability, an issue of the maintenance process, which is an important way to improve production through increased availability of functional machinery and subsequent minimization of the total production cost. Spare parts estimation based on machine reliability characteristics and operating environment is performed. The study uses an improved statistical-reliability (S-R) approach which incorporates the system/machine operating environment information in systems reliability analysis. For this purpose, two methods of Poisson process and renewal process are introduced and discussed. The renewal process model uses a multiple regression type of analysis based on Cox's proportional hazards modeling (PHM). The parametric approaches with baseline Weibull hazard functions and time-independent covariates are considered, and the influence of operating environment factors on this model is analyzed. The outputs represent a significant difference in the required spare parts estimation when considering or ignoring the influence of the relevant system operating environment. The difference is significant in the sense of spare parts forecasting and inventory management which can enhance the parts and consequently machine availability, leading to economical operation and savings.

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“…The temperature field and the thermal deformation of the workpiece are heterogeneous and nonlinear because of the moving heat source. Make the following assumptions in order to simplify the calculation process on the ball screw processing [3,4,5].…”

Section: Introduction Of the Screw Thread Hard Millingmentioning

confidence: 99%

Temperature Field Simulation of Ballscrew Whirlwind Milling

Song

Liu

et al. 2012

AMR

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Ball screw is the key parts of NC machine, precise instrument and many kinds of mechanical devices. Whirlwind milling is a new and effective thread manufacture technology. This article studies the internal heat conduction equation of whirlwind milling ball screw based on Heat Transfer, calculates ANSYS simulation result. The simulation results show that the surface temperature distribution rule and internal temperature distribution rule of a ballscrew is consistent. The article analyzes the influence factors of the thermal elongation. It provides a basis for compensating the thermal deformation error of whirlwind milling ballscrew.

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Application of Fractal in Machine Downtime Control

Cited by 5 publications

References 17 publications

Maintenance downtime evaluation in a process bottling plant

Maintenance downtime evaluation in a process bottling plant

Spare Parts Estimation for Machine Availability Improvement Addressing Its Reliability and Operating Environment — Case Study

Temperature Field Simulation of Ballscrew Whirlwind Milling

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