This content is not included in
your SAE MOBILUS subscription, or you are not logged in.
A Simulation-Based Approach to Incorporate Uncertainty in Reliability Growth Planning (RGP)
Technical Paper
2020-01-0742
ISSN: 0148-7191, e-ISSN: 2688-3627
This content contains downloadable datasets
Annotation ability available
Sector:
Language:
English
Abstract
The development of complex engineering systems often encounters various challenges in terms of meeting New Product Development (NPD) assigned budget, launch time, and system performance goals. Most of the NPD processes have been experiencing challenges to meet these goals within an increasingly competitive global market environment. These challenges become more complicated to manage when the development process is long with different sources of uncertainty. Despite decades of industrial experience and academic research efforts in managing NPD processes, it is observed that designing and developing increasingly complex systems, e.g., automotive, is still subjected to significant cost overrun, schedule delays, and functional issues during early design stages.
To provide a Reliability Growth Planning (RGP) model, several inputs are required, e.g., the initial reliability estimation, the reliability goal, test recourses, and the duration of the design or test period. These inputs can be estimated by utilizing the historical data from previous reliability practices, provided that the usage, design, and reliability practice conditions are almost similar. However, providing one deterministic value for the input parameters of the reliability growth planning model is challenging since there are many uncertainties involved in the planning process. Most of the existing RGP models are deterministic models in nature. Therefore, the current models lack in incorporating the uncertainty associated in the model input parameters. This RGP model deficiency leads to unrealistic, and in many cases, impractical Reliability Growth (RG) plans. To tackle this issue, this paper presents an approach to RGP that considers the uncertainty associated with the underlying rate of occurrence of concern and other associated planning parameters. Considering the uncertainty in the RG planning allows for more informed decision-making regarding reliability improvement.
The proposed reliability growth planning approach is an extension of current reliability growth planning models used in the reliability growth literature while modeling different sources of uncertainty that exists in the reliability growth planning models. In this paper, the current reliability growth models are enhanced with the Monte Carlo Simulation (MCS) approach. In this step, the probabilistic input parameters are introduced to the deterministic reliability growth models. A probability distribution is defined for each input parameter used in the reliability growth models. Considering probability distributions in the reliability calculation, a Monte Carlo simulation approach is developed to incorporate the probabilistic nature of the reliability estimation. Therefore, the reliability calculation is iterated, i.e., simulated, thousands of times, while in each iteration of the calculation, different values are generated for the probabilistic input parameters of the model. Through this simulation process, all possible scenarios of the reliability growth process are considered, and therefore, more realistic reliability growth plans are generated. The result is a range of various reliability growth curves which can be used as a reliability growth plan curve. The proposed approach is demonstrated through a numerical example.
Recommended Content
Technical Paper | Scheduling Analysis and Optimization for Safety-Critical Automotive Systems |
Magazine Issue | Automotive Engineering: April 1, 2014 |
Technical Paper | Modular Vehicle Architectures Using Integration Analysis Techniques |
Authors
Topic
Citation
Mobin, M. and Hijawi, M., "A Simulation-Based Approach to Incorporate Uncertainty in Reliability Growth Planning (RGP)," SAE Technical Paper 2020-01-0742, 2020, https://doi.org/10.4271/2020-01-0742.Data Sets - Support Documents
Title | Description | Download |
---|---|---|
Unnamed Dataset 1 |
Also In
References
- Shahraki , A.F. and Yadav , O.P. System Reliability Optimization Considering Probabilistic Common-Cause Failures and Uncertainty IIE Annual Conference: Proceedings of Institute of Industrial and Systems Engineers (IISE) 2015 Nashville, USA 2246 2253
- Seif , J. and Rabbani , M. Component Based Life Cycle Costing in Replacement Decisions Journal of Quality in Maintenance Engineering. 20 4 436 452 2014
- Shahraki , A.F. and Noorossana , R. Reliability-Based Robust Design Optimization: A General Methodology Using Genetic Algorithm Computers & Industrial Engineering 74 199 207 2014
- Duane , J. Learning Curve Approach to Reliability Monitoring IEEE Transact. on Aerospace 2 2 563 566 1964
- Crow , L.H. Reliability Analysis for Complex, Repairable Systems Reliability and Biometry Proschan , F. and Serfing , R.J. SIAM 1974 379 410
- Crow , L.H. Evaluating the Reliability of Repairable Systems Proc. of the Annual Reliability and Maintainability Symposium (RAMS) 1990 275 279
- Crow , L.H. Confidence Intervals on the Reliability of Repairable Systems Proc. of the Annual Reliability and Maintainability Symp. (RAMS) 1993 126 134
- Quigley , J. and Walls , L. Confidence Intervals for Reliability-Growth Models with Small Sample-Sizes IEEE Transact. on Reliability 52 2 257 262 2003
- Guo , H. and Dronzkowski , D. On Establishing an Effective Reliability Growth Program: Planning and Data Analysis International Applied Reliability Symposium 2016 San Diego, CA, North America
- Hijawi , M. , Badiei , S. , and Water , N. Event Based System Reliability Proc. of the Annual Reliability and Maintainability Symp. (RAMS) 2018
- Xie , M. and Zhao , M. Reliability Growth Plot-an Underutilized Tool in Reliability Analysis Microelectronics Reliability 36 6 797 805 1996
- Walls , L. and Quigley , J. Learning to Improve Reliability During System Development European Journ. of Operation Research 119 2 495 509 1999
- Li , Z. and Mobin , M. A DFMEA-based Reliability Prediction Approach in Early Product Design Proceeding of Reliability and Maintainability Symposium (RAMS) 2018
- Mobin , M. Reliability Modeling and Optimization of New Product Development (NPD) Process 2017
- Mobin , M. and Li , Z. An Integrated Approach to Plan the Design Verification and Validation Activities for the New Product Reliability Improvement Proceeding wof Reliability and Maintainability Symposium (RAMS) 2018
- Li , Z. , Mobin , M. , and Keyser , T. Multi-Objective and Multi-Stage Reliability Growth Planning in Early Product-Development Stage IEEE Transactions on Reliability 65 2 769 781
- Mobin , M. , Li , Z. , and Komaki , G.M. A Multi-Objective Approach for Multi-Stage Reliability Growth Planning by Considering the Timing of New Technologies Introduction IEEE Transaction on Reliability 66 1 97 110
- Heydari , M.H. , Sullivan , K.M. , and Pohl , E.A. Optimal Allocation of Testing Resources in Reliability Growth IIE Annual Conference. Proceedings 2014
- Heydari , M. and Sullivan , K.M. Robust Allocation of Testing Resources in Reliability Growth Reliability Engineering & System Safety 2017
- Heydari , M. and Sullivan , K.M. An Integrated Approach to Redundancy Allocation and Test Planning for Reliability Growth Computers & Operations Research 92 182 193
- Coit , D.W. Economic Allocation of Test Times for Subsystem-level Reliability Growth Testing IIE Transact. 30 12 1143 1151 1998
- Johnston , W. , Quigley , J. , and Walls , L. Optimal Allocation of Reliability Tasks to Mitigate Faults During System Development IMA Journ. of Management Mathematics 17 2 159 169 2006
- Jin , T. and Wang , H. A Multi-Objective Decision Making on Reliability Growth Planning for In-Service Systems Proc. of the IEEE Internat. Conf. on Systems, Man, and Cybernetics (SMC) 4677 4683 2009
- Jin , T. , Liao , H. , and Kilari , M. Reliability Growth Modeling for In-Service Electronic Systems Considering Latent Failure Modes Microelectronics Reliability 50 3 324 331 2010
- Jin , T. , Yu , Y. , and Huang , H.-Z. A Multiphase Decision Model for Reliability Growth Considering Stochastic Latent Failures IEEE Transact. on Systems, Man and Cybernetics 43 4 958 966 2013
- Vahdat , V. , Griffin , J.A. , Stahl , J.E. , and Yang , F.C. Analysis of the Effects of EHR Implementation on Timeliness of Care in a Dermatology Clinic: A Simulation Study Journal of the American Medical Informatics Association 2018