Reliability Engineering Opportunities in Industry 4.0

Main Article Content

Manuel Baro-Tijerina
Manuel Piña-Monarrez
Aida Yadira Reyes-Escalante


Industry 4.0 is based on the internet of things, this means, that in industries or companies the value chain, including processes, products, hardware, and software, among others, exists the necessity to implement new knowledge technologies to implement and control Industry 4.0 interactions, in other words, with the advantages of industry 4.0 such as the used of real-time data, big data, blockchain, human-machine interaction, cyber-systems, among others, the electronic devices that allowed this interaction and electronic data interchange centralize, need to be in the highest possible reliability perform, aiming to be able to carry out all these activities safely and effectively. In this research, the objective is to introduce some general advantages of Industry 4.0 and how reliability engineering is an important ally in the performance of the functions of Industry 4.0. Then, this manuscript presents the necessary knowledge and applications of reliability engineering that can be implemented in Industry 4.0 as stress-strength analysis in the case of equal shape parameters stress-strength analysis ; Nonnormal capability index and Weibull Capability index, by using Weibull++ Software and mathematical procedure. Another target of this research is to demonstrate that by using reliability engineering it is possible to have better control in such a way that efficiency and productivity stay and even can increases. Also, reliability engineering represents security and stable processes. Finally, with the merging of Industry 4.0 and reliability engineering, the making decision process is more reliable decision-making.

Article Details

How to Cite
Baro-Tijerina, M., Piña-Monarrez, M., & Reyes-Escalante, A. Y. . (2023). Reliability Engineering Opportunities in Industry 4.0. Engineering TODAY, 2(1).
Original Scientific Papers


W. F. Casico and R. Montealegre, “How Technology Is Changing Work and Organizations”, Annual Review of Organizational Psychology and Organizational Behaviour, Vol. 3(1), pp. 349-375,, (2016)

M. Da Bromida, “The Big Data World: Benefits, Threats and Ethical Challenges”, Ethical Issues in Covert, Security and Surveillance Research, pp. 71-91,, (2021)

V. Alcácer and V. Cruz-Machado, “Scanning the Industry 4.0: A Literature Review on Technologies for Manufacturing Systems”, Engineering Science and Technology, an International Journal, Vol. 22(3), pp. 899–919,, (2019)

M. Javaid, A. Haleem, R. P. Singh, R. Suman and E. S. Gonzalez, “Understanding the Adoption of Industry 4.0 Technologies in Improving Environmental Sustainability”, Sustainable Operations and Computers, Vol. 3, pp. 203–217,, (2022)

L. Barreto, A. Amaral and T. Pereira, “Industry 4.0 Implications in Logistics: An Overview,” Procedia Manufacturing, Vol. 13, pp. 1245–1252,, (2017)

Z. You and L. Feng, “Integration of Industry 4.0 Related Technologies in Construction Industry: A Framework of Cyber-Physical System,” IEEE Access, Vol. 8, pp. 122908–122922,, (2020)

S. Kraus, S. Durst, J. J. Ferreira, P. Veiga, N. Kailer and A. Weinmann, “Digital Transformation in Business and Management Research: An Overview of the Current Status Quo,” International Journal of Information Management, Vol. 63,, (2022)

M. Baro-Tijerina, M. R. Piña-Monarrez and R. D. M. Arredondo, “Reliability Engineering in Industry 4.0,” Critical Factor in Industry 4.0, Vol. 1(4), pp. 37–72. (2021)

M. R. Piña-Monarrez, “Weibull stress distribution for static mechanical stress and its stress/strength analysis,” Quality and Reliability Engineering International, Vol. 34, pp. 229–244,, (2017)

B. Vogel-Heuser, M. Böhm, F. Brodeck, K. Kugler, S. Maasen, D. Pantförder, M. Zou, J. Buchholz, H. Bauer, F. Brandl and U. Lindemann , “Interdisciplinary Engineering of Cyber-Physical Production Systems : Highlighting the Benefits of a Combined Interdisciplinary Modelling Approach on the Basis of an Industrial Case,” Design Science, Vol. 6(5), pp. 1–36,, (2020)

H. Matyi, P. Veres, T. Banyai, V. Demin and P. Tamas, “Digitalization in Industry 4.0: the Role of Mobile Devices,” Journal of Production Engineering, Vol. 23(1), pp. 75–78,, (2020)

M. Javaid, A. Haleem, R. P. Singh, S. Rab and R. Suman, “Significance of Sensors for Industry 4.0: Roles, Capabilities, and Applications,” Sensors Int Sensors International, Vol. 2 p. 100110,, (2021)

G. Beier, A. Ullrich, S. Niehoff, M. Reißig and M. Habich, “Industry 4.0: How it is Defined From a Sociotechnical Perspective and How Much Sustainability it Includes - A Literature Review,” Journal of Cleaner Production, Vol. 259, p. 120856,, (2020)

N. H. Tran, H. S. Park, Q. V. Nguyen and T. D. Hoang, “Development of a Smart Cyber-Physical Manufacturing System in the Industry 4.0 Context,” Applied Sciences, Vol. 9(16), pp. 1–26,, (2019)

B. Lion, F. Arbab and C. Talcott, “A Semantic Model for Interacting Cyber-Physical Systems,” 14th Interaction and Concurrency Experience (ICE 2021), Vol. 347, pp. 77–95,, (2021)

M. Tschandl, C. Ficher and E. Chapotot, “Definition of Industry 4.0”, Industry 4.0: A Comprehensive Approach -Main Features and Impacts on SMEs, 2021, pp. 10–14,

U. Sivarajah, M. M. Kamal, Z. Irani and V. Weerakkody, “Critical Analysis of Big Data Challenges and Analytical Methods,” Journal of Business Research, Vol. 70, pp. 263–286,, (2017)

A. Banik and S. K. Bandyopadhyay, “Big Data-A Review on Analysing 3Vs,” Journal of Scientific and Engineering Research, Vol. 3(1) (2016)

A. Gandomi and M. Haider, “Beyond the Hype: Big Data Concepts, Methods, and Analytics,” International Journal of Information Management, Vol. 35(2), pp. 137–144,, (2015)

J. M. Cavanillas, E. Curry, W. Wahlster, “The Big Data Value Opportunity. In: Cavanillas, J., Curry, E., Wahlster, W., (eds) New Horizons for a Data-Driven Economy,” Springer, Cham.,, (2016)

L. Cai and Y. Zhu, “The Challenges of Data Quality and Data Quality Assessment in the Big Data Era,” Data Science Journal., Vol. 14,, (2015)

S. F. Fam, N. Ismail and W. L. Shinyie, “The Magnitude of Big Data 5vs in Business Macroclimate,” Business, Computer Science, Vol. 8(1), pp. 497–503 (2019)

F. Casino, T. K. Dasaklis and C. Patsakis, “A Systematic Literature Review of Blockchain-Based Applications: Current Status, Classification and Open Issues,” Telematics and Informatics, Vol. 36, pp. 55–81,, (2019)

D. Przytarski, C. Stach, C. Gritti and B. Mitschang, “Query processing in blockchain systems: Current state and future challenges,” Future Internet, Vol. 14(1), pp. 1–31,, (2022)

C. Elisabetta, Z. Baltico, D. Catalano, D. Fiore and R. Gay, “Ouroboros: A Provably Secure Proof-of-Stake Blockchain Protocol,” CRYPTO 2017: Advances in Cryptology – CRYPTO 2017, Vol. 10403, pp. 357–388,, (2017)

U. Bodkhe, S. Tanwar, K. Parekh, P. Khanpara, S. Tyagi, N. Kumar and M. Alzab, “Blockchain for Industry 4.0: A Comprehensive Review,” IEEE Access, Vol. 4, pp. 1–37, (2020)

R. M. Amaya-Toral, M. R. Piña-Monarrez, R.M. Reyes-Martinez, J. de la Riva-Rodriguez, E. R. Poblano-Ojinaga, J. Sánchez-Leal, K. C.Arredondo-Soto, “Human–Machine Systems Reliability: A Series–Parallel Approach for Evaluation and Improvement in the Field of Machine Tools,” Applied Science, Vol. 12(3),, 2022

O. A. Omoya, K. A. Papadopoulou and E. Lou, “Reliability Engineering Application To Pipeline Design,” International Journal of Quality & Reliability Management, Vol. 36(9), pp. 1644–1662,, (2019)

J. W. Veile, D. Kiel, J. M. Müller and K. I. Voigt, “Lessons Learned From Industry 4.0 Implementation in the German Manufacturing Industry,” Journal of Manufacturing Technology Management, Vol. 31(5), pp. 977–997,, (2019)

K. Govindan, K. Zeng and P. Mohapatra, “Probability Density of the Received Power in Mobile Networks,” IEEE Transactions on Wireless Communications, Vol. 10(11), pp. 3613–3619,, (2011)

T. P. Raptis, A. Passarella and M. Conti, “Data Management in Industry 4.0: State of the Art and Open Challenges,” IEEE Access, Vol. 7, pp. 97052–97093,, (2019)

A. R. Kumar and K. V, “A Study on System Reliability in Weibull Distribution,” IJIREEICE, Vol. 5(3) , pp. 38–41,, (2017)

M. R. Piña, M. Baro-Tijerina and J. F. Ortiz-Yañez, “Unbiased Weibull Capabilities Indices Using Multiple Linear Regression,” Quality and Reliability Engineering International, Vol. 33(8), pp. 1915–1920,, (2017)

J. F. Ortiz-Yañez and M. R. Piña-Monarrez, “Discrimination Between the Lognormal and Weibull Distributions by Using Multiple Linear Regression,” DYNA, vol. 85(205), pp. 9–18,, (2018)

C. Liu, R. W. White and S. Dumais, “Understanding Web Browsing Behaviors Through Weibull Analysis of Dwell Time,” SIGIR '10: Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval, pp. 379–386,, (2010)

T. Kemsley, “Availability and Reliability Analysis of Offshore Production Systems.,” International Journal of Control Theory and Applications, Vol. 10(18),, (2017)

M. A. Farsi and E. Zio, “Industry 4.0: Some Challenges and Opportunities for Reliability Engineering,” International Journal of Reliability, Risk and Safety: Theory and Application., Vol. 2(1), pp. 23–34,, (2019)

M. Andrzej, “Uncertainty in the Sphere of the Industry 4.0 – Potential Areas To Research Business, Management and Economics Engineering, Vol. 14(2), pp. 275–291,, (2016)

L. C. Méndez-González, R. Ambrosio-Lazaro, I. Rodríguez-Borbon and A. Alvarado-Iniesta, “Failure Mode and Effects Analysis of Power Quality Issues and Their Influence in the Reliability of Electronic Products,” Electrical Engineering, Vol. 99(1), pp. 93–105,, (2017)

E. Álvarez, P. J. Moya-Férnandez, F. J. Blanco-Encomienda and J. F. Muñoz, “Methodological Insights for Industrial Quality Control Management: the Impact of Various Estimators of the Standard Deviation on the Process Capability Index,” Journal of King Saud University - Science, Vol. 27(3), pp. 271–277,, (2015)

H. K. Mohajan, “Two Criteria for Good Measurements in Research: Validity and Reliability,” Annals of Spiru Haret University. Economic Series, Vol. 17(4), pp. 59–82,, (2017)

M. Tortorella, “Service Reliability Theory and Engineering, I: Foundations,” Quality Technology & Quantitative Management, Vol. 2(1), pp. 1–16,, (2005)

M. Baro-Tijerina, M. R. Piña-Monarrez and R. D. M. Arredondo, “Reliability Engineering in Industry 4.0”, Critical Factor in Industry 4.0 – A Multidisciplinary Perspective, Ciudad Juárez: El Colegio de Chihuahua, 2021, pp. 73–94,

M. R. Piña-Monarrez, “Weibull Stress Distribution for Static Mechanical Stress and its Stress/Strength Analysis,” Quality and Reliability Engineering International, Vol. 34(2), pp. 229–244,, (2018)

E. Rosemount, H. P. Transmitter, and T. Stewart, “Failure Modes, Effects and Diagnostic Analysis”, 2nd ed., Shakopee, (2016)

M. Baro-tijerina and G. Duran-medrano, “Stress / Strength Models to Estimate Systems Reliability R ( t ) = P ( x < y ),” International Journal of Engineering Research & Technology, Vol. 7(3), pp. 356–362, (2018)

F. Menan, A. P-a and M. François, “The Stress-Strength Interference Method Applied to Fatigue Design: the Independence of the Random Variables,” Procedia Engineering, Vol. 133, pp. 746–757,, (2015)

B. A. P. Basu, “Stress-Strength Model,” Encyclopedia of Statistics in Quality and Reliability, pp. 1–6,, (2008)

G. Levitin and M. Finkelstein, “A New Stress–Strength Model for Systems Subject to Stochastic Shocks,” Proc. Inst. Mech. Eng. Part O J. Risk Reliab., p. 1748006X1668954,, (2017)

S. Ali, S. Ali, I. Shah, and G. Farooq, “Reliability Analysis for Electronic Devices Using Generalized Exponential Distribution,” IEEE Access, Vol. 8, pp. 108629-108644, (2020)

D. H. Collins and R. L. Warr, “Failure Time Distributions for Complex Equipment,” Quality and Reliability Engineering International, Vol. 35(1), pp. 146–154,, (2019)

P. Hilber, “Component Reliability Importance Indices for Maintenance Optimization of Electrical Networks” (RCM), (2005)

D. Horváth and R. Z. Szabó, “Driving Forces and Barriers of Industry 4.0: Do Multinational and Small and Medium-Sized Companies Have Equal Opportunities?,” Technological Forecasting and Social Change, Vol. 146, pp. 119–132,, (2019)

N. H. M. Zaidin, M. N. M. Diah and S. Sorooshian, “Quality Management in Industry 4.0 Era” J. Manag. Sci., Vol. 1(2), pp. 182–191,, (2018)