Any industrial company has to assess the variation associated with its measurement processes to ensure the reliability of its data. For that you need to study the performance of your measurement systems, in terms of linearity, bias, repeatability and reproducibility and stability.

This is a critical issue for automotive industry suppliers, especially those certified by the IATF 16949: 2016 standard (replaces ISO / TS 16949) which defines the requirements of a quality management system for companies in the automotive sector, and the analysis of the measurement system (MSA – Measurement System Analysis) a mandatory requirement.

According to the “ISO Survey 2016”, more than 67,000 (67,358) companies worldwide are ISO/TS 16949 certified, with the following distribution: around 40,000 (39,986) in Asia and the Pacific (59.4% ), approximately 13 thousand (12,786) in Europe (19.0%) and the remainder (6,389) in North America (9.5%).

From 2010 to 2016 there was an average increase of 7% per year. This growth trend allows us to understand the market potential that exists for this type of solution.

In response to the challenges of the market and of our clients certified by IATF 16949:2016, SINMETRO created a multidisciplinary team to develop this RTD project, which is made up of designers, researchers, programmers and project managers from SINMETRO and researchers from the Universidade Nova de Lisboa.

This team (fig. 1) had the collaboration of three test companies, Novares (a plastic injection multinational, 1st and 2nd line supplier to the automotive industry), PrioEnergy (biodiesel production) and AFERYMED (metrological verification agency), who supported the team by providing specifications for the system, data from real cases, validating the design prototype and carrying out tests. 

Figure 1: Project team and test companies.

This contribution is critical for accelerating the development process, adapting the solution to the real needs of the market and mainly to guarantee scalability, ensuring that it responds to different modus operandi of organizations.

After a review of the state of the art, mainly in terms of data storage and accessibility strategies and respective statistical treatment, as well as the connection with equipment, networks and databases and UI/UX principles to be adopted to ensure simple use of the system, the team defined the project vision with the following three requirements: 

1. Be a web/cloud system that does not require a local technological infrastructure, reducing installation, maintenance and updating costs.

2. Be a responsive application, 100% user configurable and easy to use, to ensure a scalable product that can be used by any type of company that needs to validate their mediation systems.

3. Be a system that allows integration with equipment and other applications.

 To develop this vision, the team defined and implemented the technological infrastructure (Fig. 2), on a web/cloud based business model. 

Figure 2: ACCEPT MSA web/cloud infrastructure.

This model does not need local servers, as the data is stored in a cloud, public or private, as a pay-as-you-go pricing model, which allows a drastic reduction in fixed and variable costs, as well as an increase in speed. , security, flexibility and system availability 24/7.

The backend of this infrastructure is based on an applicational API and on MySQL database in which all the logical elements of the ACCEPT MSA software were programmed.

The algorithms of the MSAs studies, developed in the investigation process, and all the statistical calculations of the ACCEPT MSA are programmed in the Statistics API, developed in the Python language.

To ensure the connection to different devices, the API Devices and the Link application were developed, in the node.js language, where several IoT protocols were programmed.

The ACCEPT MSA frontend was developed using the Vue.js, Javascript and Laravel frameworks.

For the development of this product, the following methodology was adopted, comprising 10 steps:

1. Define the strategy and IT infrastructure;

2. Understand data flow and traceability requirements;

3. Implement IoT data network and develop API Devices and Link application to ensure connection with different types of equipment;

4. Define the main KPIs to measure the performance of MSA processes;

5. Design of ACCEPT MSA software according to UI/UX principles;

6. Continuously validate the software design prototype with the testing companies;

7. Develop the ACCEPT MSA software according to a web/cloud based approach and according to the technological strategy described above;

8. Simultaneously develop the API Statistics, in Python language, to implement the algorithms for MSA studies and statistical data analysis;

9. Continuously test the software in a laboratory environment (simulation) and in a real environment (test companies);

10. Develop dashboards that allow real-time management of the generated “big data”, transforming data into knowledge and value;

From this research work, we have the following results that are scalable and exportable in nature:

1. Web/cloud based ACCEPT MSA application;

2. API Statistics;

3. API Devices and Link application;

4. New algorithms for MSA studies;

5. ACCEPT MSA Style Guide, developed according to UI/UX principles;

The present work was the subject of scientific dissemination with the presentation of the paper “A Web and Cloud-Based Measurement System Analysis Tool for the Automotive Industry”, which was subjected to a “peer review” process, on July 12th in Stockholm at ICIMT 2018 conference: 20th International Conference on Industrial Management and Technology. – Barros, C. A., Barroso, A.P., “A Web and Cloud-Based Measurement System Analysis Tool for the Automotive Industry”, 20th International Research Conference Proceedings, Part IV, pp. 501-505, Stockholm Sweden, July 2018.

MSA project distinguished with the award for best article

Best Paper Award ICIMT 2018

Following its participation in the ICIMT 2018: 20th International Conference on Industrial Management and Technology, promoted by WASET – World Academy of Science Engineering and Technology, the MSA project was distinguished with the Best Paper Award, evidencing the quality of the submitted paper.