BSH Electrodomésticos
Automatic document classification
Customer
BSH is a global manufacturer of household appliances, being a national and European leader with more than 40 manufacturing plants around the world, as well as having a significant market share worldwide. Its production focuses on the commercial brands Bosch, Siemens, Balay, Gaggenau and Neff.
International project awards received by BSH Electrodomésticos España:
Challenge
BSH needed to streamline and automate its analysis of after-sales technical services carried out by the Quality Management Department, as many of these processes were carried out manually.
This caused, for example at the Esquíroz factory (Navarra):
- 10 days of work per month by an engineer from the department to collect data from the repair bulletins previously filled in by the technicians, classify them and cross-reference them with production data, in order to analyse the quality indexes.
- Impossibility of manually classifying and analysing all the technical services of the previous month.
Results
- Significant increase in the efficiency of the Quality Department, saving almost 10 working days per month of an Engineer in classification and analysis of technical repair services.
- Elimination of bottlenecks by not depending on the Quality Management Department for access to relevant information.
- Significant improvement in quality index analysis, allowing new strategies to be defined and decisions to be made quickly.
- Thanks to automated processes, it is now possible to perform classification and analysis of virtually all technical services of the month.
- Being able to classify technical services in many more languages than before, as the translation is also automated.
- This developed solution is fully scalable to the rest of the BSH Group Production Plants, increasing the total benefits of the solution.
Solution
Automatic Classification Algorithms for Technical Repair Services based on the following Technologies:
- Machine Learning (Inteligencia Artificial).
- Deep Learning (Neural Networks).
- Python, R.
- NLP (Natural Language Processing).
- Text Mining .
- AWS Translate Service.
Integrated visualisation of both the results obtained from the Classification process and other sources of Production Data related to Quality Indices, all according to our client’s requirements and considering multiple levels of analysis. This Solution was based on the following Technology:
- Tableau Desktop/Server, one of the leading BI tools in the market.
The Data used in both Solutions were, mainly:
- Technical Repair Service History.
Production Data related to Quality Management.
Testimonials
Unai Esparza Baquer
Head of Field Quality Analysis at BSH Electrodomésticos España, Esquiroz Factory (Navarra)
“In order to implement the ARIS project for the automatic classification of repair services and market quality analysis at BSH, we decided two years ago to contact PredictLand.
Now that ARIS is operational, having achieved its objectives and won awards such as the BSH Innovation Award 2020 and the Excellence Award 2020 from the German Chamber of Commerce, we can see that the decision to engage with PredictLand in this venture was the right one.
Without their extensive technical knowledge of data science, we would not have succeeded. In addition, we are grateful for the high degree of customer orientation shown by PredictLand in making the effort to familiarise with our internal jargon and the resources we have at our disposal at BSH, exploring the work strategies that best adapt to the internal functioning of our company and offering training support in Data Science to the BSH staff linked to the project.
It should also be noted that the team has worked in a permanent climate of trust based on transparency in terms of project feasibility analysis, cost estimation, risk identification and detailed and regular monitoring of executed and pending tasks.
During this time we have created a solid and efficient working team that extends beyond our company and from which I expect great success in the future as well.“
Francisco Javier Alemán Ezcaray
Head of Quality for Refrigerators and Dishwashers at BSH Electrodomésticos España, Esquíroz Factory (Navarra)
“In 2018, the head of market quality in my department came to my site to talk to me about the infinite possibilities that a Machine Learning algorithm could give us when it came to analysing the data that the technical service collected on the incidents of our devices in the market. At that moment, the idea was only in his head and that of Javier Orús, from PredictLand. The spark had been ignited in a training session given by Javier himself, which was attended by members of my team.
We got down to work, in a very close collaboration between BSH and PredictLand, where we contributed our knowledge of our market and appliances, as well as our needs, and PredictLand a tremendous expertise and a very high level of understanding of the challenge we had set for.
As a result, we developed a project that gives us much more accurate data than we had before, in much less time and easily editable and understandable by other areas of BSH that until then had not dived into what was happening to our appliances in the market.
The qualitative leap in our analysis is not measurable. The progress is so great that I cannot compare it with the previous situation. And all thanks to the great professionals at PredictLand, where not only their knowledge has been key, but also their attitude, closeness and constant support.
We already have in mind a battery of projects arising from the much we have learned with this project about the infinite possibilities of artificial intelligences.”
Borja Lara López
I4.0 Coordinator at BSH Electrodomésticos España.
“During the time that I have shared with PredictLand and its members in the development and execution of a project of high value for my company, I have had the privilege of working with people of a high technical capacity who have not only contributed very positively to the good development of the activities but have also contributed a lot of knowledge to the people who have participated in it.
Not only the aptitude of this group of professionals is good, but also their attitude is exemplary. During the course of the project, we encountered many obstacles that were tackled with a very intelligent strategy, understanding the reality of our company and, above all and very importantly, with a magnificent flexibility to adopt other ways of working or tools that until then had been unknown to them.
It has not only been an enriching experience on a technical level, but also on a personal level, which has not failed to provide us with value in multiple fields.”
