Casting Clinic #11
The 11th edition of the Casting Clinic sessions, dedicated to the theme "Data Management", was held on May 4 at FEUP's facilities.
The opening session was made by Professor Luís Filipe Malheiros, CITNM board member and Professor at the Department of Metallurgical and Engineering Materials at FEUP, who welcomed the participants, introduced the theme of the session and the speakers.
The first intervention was made by Professor Vera Miguéis, PhD in Industrial Engineering and Management, whose academic and professional background are closely related to data management. She shared a global approach to the theme, which is transversal to all areas of activity and should serve the purpose of sustaining decision making through the collection and analysis of information. According to the invited speaker, data management allows the discovery of patterns that were until then unknown, through the application of mathematical tools to treat the collected data, allowing a "microscopic view" of the process.
Data management is currently vital to the competitiveness of companies, since it allows them to optimize processes, simplify operations and innovate the way they look and conduct business.
A good cycle of data management should consist of the following steps:
- Identification / problem formulation;
- Information preparation;
- Exploration / analysis of information;
- Information selection and transformation;
- Construction of the mathematical model;
- Validation of the model;
- Implementation of the model;
- Evaluation / monitoring of results and continuous improvement of the model.
In the end, she concluded that data management should be used preventively in order to anticipate solutions, not just reactively, in order to solve the existing problems.
Such was followed by Sakthi’s Portugal practical case presentation on its database implementation and system of preventive control of production, by the mentor and promoter of the project, Fernando Vilela.
Because of the constant need to analyse information stored in large paper files, and because of the difficulty of storing computer data that would have to be fed manually, in 2001 Sakthi Portugal developed a solution that would automatically feed a computerized database, where there would be all the variables of the process. So, it has adapted and replaced equipment to allow the automatic collection and transfer of data to a centralized database. This process gave birth to the DataPro system.
DataPro, whose main function was to store data, quickly evolved to statistically treat the information and alert users when a certain process parameter got out of the predefined range, forcing a corrective action. This tool has also produced the necessary reports for the development of the activity and it fits as a user support tutorial, as it also includes a Process Control Plan module. It instructs users on corrective actions to be taken in different situations. Thus, DataPro currently serves the following purposes:
- Deviation identification;
DataPro’s success and usefulness inspired Sakthi Portugal to dream higher: to predict the quality of the pieces before being cast.
Thus, based on the information stored in DataPro, Sakthi Portugal, together with IK4-Azterlan, developed a new software - Olimpo - which, based on mathematical models, can predict the results of any leakage by proximity of historical data.
Olimpo, implemented in 2016, analyses the data coming from the production, makes a predictive control of the process, generates knowledge and has the ultimate objective to reach perfection: zero defective components, and therefore, zero customer complaints.
After a productive discussion session, the speakers finished the session leaving behind some practical advice to the participants:
- It is not possible to manage without indicators! It is essential to focus on the collection and data management;
- Resilience. These processes can be time-consuming to produce useful results, so companies, in spite of their leaders (# 1), must resist the temptation to give up, with determination and work capability;
- The cost of implementing data management should not be seen as a condition for deciding on the acquisition of the system, once the experience of speakers indicates that companies implementing data management achieve substantially better results than others.