Technology selection for Industry 4.0 oriented condition-based monitoring system: A case study in the paper mills industry

Diego Cabrera, Mariela Cerrada, Jean Carlo Macancela, Julio Siguencia, René Vinicio Sánchez

Research output: Contribution to journalConference articlepeer-review

2 Scopus citations


Today, we have many options for hardware and software technology solutions for the migration of the manufacturing sector to an industry 4.0. However, there are many cases in which the adoption of new technologies has been slowed mainly due to uneven growth in the industry, little standardization, poor systems’ integration, lack of knowledge, and the lack of providers who understand the real needs of companies. The purpose of this work is to present a methodology for selecting the proper technology that was developed after characterizing and quantifying the industry’s requirements. Our methodology presents criteria for evaluating and selecting technology providers that focus on four dimensions: technical criteria, purchase criteria, additional services for the operation of the products, and operating costs. This methodology represents a practical way to qualify technology providers, assigning them a quantitative score so that the decision-making process is much faster, more convincing, and compelling, especially when adopting new technology. The methodology was built and used into a paper mill for selecting sensor suppliers to implement a condition monitoring system that captures vibration signals at different points of paper presses. The evaluation was successful, resulting in a winning provider being selected and the IoT sensor-based system implemented.

Original languageEnglish
Pages (from-to)211-216
Number of pages6
Issue number19
StatePublished - 1 Jul 2022
Event5th IFAC Workshop on Advanced Maintenance Engineering, Services and Technologies, AMEST 2022 - Bogota, Colombia
Duration: 26 Jul 202229 Jul 2022

Bibliographical note

Funding Information:
This work is supported in part by the MOST Science and Technology Partnership Program (KY201802006), and National Research Base of Intelligent Manufacturing Service Chongqing Technology and Business University.

Publisher Copyright:
Copyright © 2022 The Authors.


  • Condition-Based Maintenance
  • Evaluation Criteria
  • Industry 4.0
  • IoT Sensors
  • Manufacturing
  • Paper Factory
  • Technology Selection


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