Integrated reliability and maintainability analysis of Computerized Numerical Control Turning Center considering the effects of human and organizational factors

2019 ◽  
Vol 26 (1) ◽  
pp. 87-103
Author(s):  
Rajkumar Bhimgonda Patil
Keyword(s):  
Organizational Factors ◽  
Numerical Control ◽  
Content Type ◽  
Failure Data ◽  
Turning Center ◽  
Maintainability Analysis ◽  
Human And Organizational Factors ◽  
Mean Time ◽  
Best Fit ◽  
Field Failure

Purpose Reliability, maintainability and availability of modern complex engineered systems are significantly affected by four basic systems or elements: hardware, software, organizational and human. Computerized Numerical Control Turning Center (CNCTC) is one of the complex machine tools used in manufacturing industries. Several research studies have shown that the reliability and maintainability is greatly influenced by human and organizational factors (HOFs). The purpose of this paper is to identify critical HOFs and their effects on the reliability and maintainability of the CNCTC. Design/methodology/approach In this paper, 12 human performance influencing factors (PIFs) and 10 organizational factors (OFs) which affect the reliability and maintainability of the CNCTC are identified and prioritized according to their criticality. The opinions of experts in the fields are used for prioritizing, whereas the field failure and repair data are used for reliability and maintainability modeling. Findings Experience, training, and behavior are the three most critical human PIFs, and safety culture, problem solving resources, corrective action program and training program are the four most critical OFs which significantly affect the reliability and maintainability of the CNCTC. The reliability and maintainability analysis reveals that the Weibull is the best-fit distribution for time-between-failure data, whereas log-normal is the best-fit distribution for Time-To-Repair data. The failure rate of the CNCTC is nearly constant. Nearly 66 percent of the total failures and repairs are typically due to the hardware system. The percentage of failures and repairs influenced by HOFs is nearly only 16 percent; however, the failure and repair impact of HOFs is significant. The HOFs can increase the mean-time-to-repair and mean-time-between-failure of the CNCTC by nearly 65 and 33 percent, respectively. Originality/value The paper uses the field failure data and expert opinions for the analysis. The critical sub-systems of the CNCTC are identified using the judgment of the experts, and the trend of the results is verified with published results.

Statistical analysis of failure data for estimating reliability, availability and maintainability of an automated croissant production line

2019 ◽  
Vol 25 (3) ◽  
pp. 452-475 ◽  
Author(s):  
Panagiotis Tsarouhas
Keyword(s):  
Production Line ◽  
Continuous Monitoring ◽  
Maintenance Strategy ◽  
Content Type ◽  
Failure Patterns ◽  
Failure Data ◽  
Correlation Tests ◽  
Line Level ◽  
Ram Analysis ◽  
Best Fit

Purpose The purpose of this paper is to compute reliability, availability and maintainability (RAM) indices to measure and improve the performance of an automated croissant production line under real working conditions. Based on this study, the authors demonstrate how RAM analysis is very useful for deciding maintenance intervals and for planning and organizing the adequate maintenance strategy. Design/methodology/approach The present work is carried out by analyzing failure and repair data based on statistical techniques. Descriptive statistics of the failure and repair data at workstation and line level were carried out. Trend and serial correlation tests validated the assumption of independence and identical distribution of the failure data were conducted. Moreover, the reliability and maintainability of both the croissant production line and its workstations have been estimated at different mission times with their best fit distribution. Findings The main objectives of the applied method are to understand the nature of the failure patterns, and to estimate the reliability and maintainability characteristics of the croissant production system in precise quantitative terms. The analysis identifies the critical points of the production line that require further improvement through effective maintenance strategy. Originality/value This study is anticipated to serve as an illuminating effort in conducting a complete RAM analysis and its effect on the performance of the system that works under real conditions. The advantage of the methodology is the continuous monitoring of the production process through appropriate indices, the utilization of which leads to a continuous cycle of improvement.

Reliability analysis of CNC turning center based on the assessment of trends in maintenance data

2017 ◽  
Vol 34 (9) ◽  
pp. 1616-1638 ◽  
Author(s):  
Rajkumar Bhimgonda Patil ◽  
Basavraj S. Kothavale ◽  
Laxman Yadu Waghmode ◽  
Shridhar G. Joshi
Keyword(s):  
Reliability Analysis ◽  
Goodness Of Fit ◽  
Numerical Control ◽  
Maintenance Cost ◽  
Repairable Systems ◽  
Content Type ◽  
Cnc Turning ◽  
Warranty Period ◽  
Turning Center ◽  
Support Cost

Purpose The paper presents reliability, maintainability and life cycle cost (LCC) analysis of a computerized numerical control (CNC) turning center which is manufactured and used in India. The purpose of this paper is to identify the critical components/subsystems from reliability and LCC perspective. The paper further aims at improving reliability and LCC by implementing reliability-improvement methods. Design/methodology/approach This paper uses a methodology for the reliability analysis based on the assessment of trends in maintenance data. The data required for reliability and LCC analysis are collected from the manufacturers and users of CNC turning center over a period of eight years. ReliaSoft’s Weibull++9 software has been used for verifying goodness of fit and estimating parameters of the distribution. The LCC of the system is estimated for five cost elements: acquisition cost, operation cost, failure cost, support cost and net salvage value. Findings The analysis shows that the spindle bearing, spindle belt, spindle drawbar, insert, tool holder, drive battery, hydraulic hose, lubricant hose, coolant hose and solenoid valve are the components with low reliability. With certain design changes and implementation of reliability-based maintenance policies, system reliability is improved, especially during warranty period. The reliability of the CNC turning center is improved by nearly 45 percent at the end of warranty period and system mean time between failure is increased from 15,000 to 17,000 hours. The LCC analysis reveals that the maintenance cost, operating cost and support costs dominate the LCC and contribute to the tune of 87 percent of the total LCC. Research limitations/implications The proposed methodology provides an excellent tool that can be utilized in industries, where safety, reliability, maintainability and availability of the system play a vital role. The approach may be improved by collecting data from more number of users of the CNC turning centers. Practical implications The approach presented in this paper is generic and can be applied to analyze the repairable systems. A real case study is presented to show the applicability of the approach. Originality/value The proposed methodology provides a practical approach for the analysis of time-to-failure and time-to-repair data based on the assessment of trends in the maintenance data. The methodology helps in selecting a proper approach of the analysis such as Bayesian method, parametric methods and nonparametric methods.

Reliability Analysis and Improvement of ATCs of CNC Lathes

2010 ◽  
Vol 37-38 ◽  
pp. 939-943 ◽  
Author(s):  
Yi Qiang Wang ◽  
Xiao Jun Wang ◽  
Shun Ming Hua
Keyword(s):  
Failure Analysis ◽  
Block Diagram ◽  
Numerical Control ◽  
Coding System ◽  
Failure Data ◽  
Cnc Lathe ◽  
Automatic Tool Changer ◽  
Automatic Tool ◽  
Set Up ◽  
Field Failure

An automatic tool changer (ATC) is one of the most important subsystems of a computerized numerical control (CNC) lathe. The field failure analysis is very important to improve the reliability of the ATC. The structure and mechanism of an ATC is briefly introduced. Its brief reliability block diagram is set up. With this understanding, through the collection of the field failure data, a coding system to code failure data is devised and a failure analysis database of CNC lathes is accrued. The failure mode and cause are analyzed to indicate the weak subsystem of the ATC. Some suggestions on improving the reliability have been proposed.

Selection of time-to-failure model for computerized numerical control turning center based on the assessment of trends in maintenance data

2018 ◽  
Vol 233 (2) ◽  
pp. 105-117 ◽  
Author(s):  
Rajkumar Bhimgonda Patil ◽  
Basavraj S Kothavale ◽  
Laxman Yadu Waghmode
Keyword(s):  
Cooling System ◽  
Electronic System ◽  
Numerical Control ◽  
Time To Failure ◽  
Failure Model ◽  
Time Data ◽  
Failure Data ◽  
Turning Center ◽  
Computerized Numerical Control ◽  
Selection Of

This article provides a generalized framework for selection of time-to-failure model based on the assessment of trends in failure and repair time data. This framework is based on modifications of existing frameworks and can be applied for binary as well as multi-state systems. The proposed framework is applied for reliability analysis of a computerized numerical control turning center. For analysis purpose, the failure data are collected for 50 computerized numerical control turning center over a period of 7 years for three different working conditions, that is, when machining material is steel, aluminum and cast iron. The data collected are then processed using the proposed framework and the best-fit distribution is found for the time-to-failure data. Furthermore, the reliable life and reliabilities of the different sub-systems are estimated. From the analysis, it is found that spindle system, computerized numerical control system, electrical and electronic system, hydraulic system and cooling system are found to be critical from reliability and maintainability point of view. The analysis presented here is expected to help the users and manufacturers of computerized numerical control turning center to estimate the reliability in accurate manner.

Maintainability analysis in shaving blades industry: a case study

2017 ◽  
Vol 34 (4) ◽  
pp. 581-594 ◽  
Author(s):  
Panagiotis Tsarouhas ◽  
George Besseris
Keyword(s):  
Production System ◽  
High Tech ◽  
Data Sets ◽  
Total Quality ◽  
Total Productive Maintenance ◽  
Content Type ◽  
Fitness Index ◽  
Maintainability Analysis ◽  
Mean Time

Purpose The purpose of this paper is to provide results for a complete maintainability analysis utilizing data sets from a production system in a shaving blades division of a large high-tech razor manufacturer. Through the illustrated case study, the authors demonstrate how to spot improvement points for enhancing availability by carrying out an equipment effectiveness analysis. Design/methodology/approach Descriptive statistics of the repair data and the best fitness index parameters were computed. Repair data were collected from departmental logs, and a preliminary screening analysis was conducted to validate their usefulness for the indicated period of 11 months. Next, the maintainability and repair rate modes for all the machines of the production system were calculated. Maintainability and availability estimations for different time periods that took in account the overall system were obtained by trying out and selecting an optimum statistical model after considering of several popular distributions. Findings Out of the five considered machines in the system, two particular units received about half of the repairs (M2 and M3). The time to repair follows a loglogistic distribution and subsequently the mean time to repair is estimated at 25 minutes at the machine level. Repair time performance is approximated at 55 minutes if the availability of the system is to attain a 90 percent maintainability. Originality/value This study is anticipated to serve as an illuminating effort in conducting a complete maintainability analysis in the much advertised field of shavers, for which on the contrary so little has been published on operational availability and equipment effectiveness. The case study augments the available pool of sources where executing maintainability studies is highlighted usually under the direction of combined total quality management and total productive maintenance programs.

A generalized model selection framework for multi-state failure data analysis

2022 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Rajkumar Bhimgonda Patil ◽  
Suyog Subhash Patil ◽  
Gajanand Gupta ◽  
Anand K. Bewoor
Keyword(s):  
Data Analysis ◽  
Reliability Analysis ◽  
State System ◽  
Numerical Control ◽  
Failure Behavior ◽  
Class Iii ◽  
Content Type ◽  
Failure Data ◽  
Binary State ◽  
Design Attribute

PurposeThe purpose of this paper is to carry out a reliability analysis of a mechanical system considering the degraded states to get a proper understanding of system behavior and its propagation towards complete failure.Design/methodology/approachThe reliability analysis of computerized numerical control machine tools (CNCMTs) using a multi-state system (MSS) approach that considers various degraded states rather than a binary approach is carried out. The failures of the CNCMT are classified into five states: one fully operational state, three degraded states and one failed state.FindingsThe analysis of failure data collected from the field and tests conducted in the laboratory provided detailed understandings about the quality of the material and its failure behavior used in designing and the capability of the manufacturing system. The present work identified that Class II (major failure) is critical from a maintainability perspective whereas Class III (moderate failure) and Class IV (minor failure) are critical from a reliability perspective.Research limitations/implicationsThis research applies to reliability data analysis of systems that consider various degraded states.Practical implicationsMSS reliability analysis approach will help to identify various degraded states of the system that affect the performance and productivity and also to improve system reliability, availability and performance.Social implicationsIndustrial system designers recognized that reliability and maintainability is a critical design attribute. Reliability studies using the binary state approach are insufficient and incorrect for the systems with degraded failures states, and such analysis can give incorrect results, and increase the cost. The proposed MSS approach is more suitable for complex systems such as CNCMT rather than the binary-state system approach.Originality/valueThis paper presents a generalized framework MSS's failure and repair data analysis has been developed and applied to a CNCMT.

Reliability Prediction Based on Field Failure Data of Guided Missile

2018 ◽  
Vol 18 (3) ◽  
pp. 250-259 ◽  
Author(s):  
Yangwoo Seo ◽  
Kyeshin Lee ◽  
Younho Lee ◽  
Jeyong Kim
Keyword(s):  
Reliability Prediction ◽  
Failure Data ◽  
Field Failure

Performance management in public universities: overcoming bureaucracy

2018 ◽  
Vol 67 (4) ◽  
pp. 736-753 ◽  
Author(s):  
Nunzio Angiola ◽  
Piervito Bianchi ◽  
Letizia Damato
Keyword(s):  
Performance Management ◽  
Public Universities ◽  
Organizational Factors ◽  
Public University ◽  
Management Systems ◽  
Management Tools ◽  
Performance Levels ◽  
Content Type ◽  
Performance Management Systems ◽  
Adoption And Implementation

Purpose Considering a micro performance perspective, the purpose of this paper is to analyze whether and to what extent the adoption of better performance management systems could improve the performance levels of a public university. Design/methodology/approach With reference to a period of four years (2011-2014), the quality of performance management systems of 29 Italian universities (response rate: 48 percent) was examined and the possible effects on performance levels of these institutions were analyzed by means of statistical methodologies (multiple regression analysis). Outcome indicators were considered. Findings The findings indicate the need to go further “measurement,” and to take care of performance “management,” especially in complex organizations as universities, where academicians identify themselves more with their professions than with the organization and where technicians and administrative employees might look at the performance-based reform with “bureaucratic eyes.” A fruitful cooperation between the professional soul and the bureaucratic one is paramount. Originality/value Studies which analyze organizational factors that could affect the adoption and implementation of performance management systems are rare, and use in prevalence qualitative methods or refer to machine bureaucracies, not many to professional ones as public universities. Moreover, the performance management literature in a public university context deepens the topic of the selection of KPIs and the focus is mainly on macro performance or on management tools for gathering and analyzing performance measures.

Adaptive neuro-fuzzy fusion of multi-sensor data for monitoring of CNC machining

Sensor Review ◽  
2017 ◽  
Vol 37 (1) ◽  
pp. 78-81 ◽  
Author(s):  
Srdjan Jovic ◽  
Obrad Anicic ◽  
Milivoje Jovanovic
Keyword(s):  
Selection Process ◽  
Spindle Speed ◽  
Cnc Machining ◽  
Numerical Control ◽  
Periodic Component ◽  
Sensor Data ◽  
Depth Of Cut ◽  
Inference System ◽  
Content Type ◽  
Neuro Fuzzy

Purpose Acoustic emission (AE) could be used for prevention and detection of tool errors in Computer Numerical Control (CNC) machining. The purpose of this study is to analyze the AE form of CNC machining operations. Design/methodology/approach Experimental measurements were performed with three sensors on the CNC lathe to collect the data of the CNC machining. Adaptive neuro-fuzzy inference system (ANFIS) was applied for the fusion from the sensors’ signals to determine the strength of the signal periodic component among the sensors. Findings There were three inputs, namely, spindle speed, feed rate and depth of cut. ANFIS was also used to determine the inputs’ influence on the prediction of strength of the signal periodic component. Variable selection process was used to select the most dominant factors which affect the prediction of strength of the signal periodic component. Originality/value Results were shown that the spindle speed has the most dominant effect on the strength of the signal periodic component.

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