Two Spanish companies create the world’s first process mining living laboratory

Written by
inverbis analytics
31 de May de 2022 Max 3 min read

Press Release

  • Inverbis is the first process mining company to have a permanent environment for generating and testing real data.

  • The ‘Living Lab’ will shorten the lead time between research and its application in real production processes.

  • Process mining helps detect inefficiencies and hidden costs in the processes of manufacturing and service companies.

Madrid, May 25, 2022.- Inverbis Analitycs, a Galician startup operating in the field of process intelligence, and Queixerias Bama (Queizuar), a leading producer of cheese with Protected Designation of Origin Arzúa- Ulloa and Tetilla, have created the world’s first process mining living lab.

“This collaboration places us in a unique position in the international market to develop approaches and methods for the practice of process mining that, with the right results, will generate value from day one,” explains Gonzalo Martín, CEO of Inverbis.

Also known as ‘Living Lab’, this laboratory will support Value Stream Mining, a technique that applies process mining to process improvement initiatives based on Value Stream Mapping, to be permanently implemented in a real business environment.

Value Stream Mapping is a methodology used to visualize, analyze, and improve the flow of products and information in a production process, from the start of the process to delivery to the customer.

In other words, the Living Lab will allow us to optimize the manufacturing processes by detecting and analyzing issues that can affect performance, operability, or efficiency, enabling us to improve production and reduce lead times and cost.

The laboratory also facilitates process intelligence R&D&I initiatives, and the development of solutions that work in a real environment.

The ultimate purpose of a ‘Living Lab’ is to test hypotheses, create reliable models, and reach conclusions that can be applied to real production environments, and then validate the results using scientific research methods .

The Inverbis-Queizuar Living Lab

The world’s first process mining ‘Living Lab’, created by Inverbis and Queizuar, is a shared R&D&I project to develop the full potential of process mining with the collaboration of university research centers and industrial optimization consultants.

This laboratory allows Queizuar to completely digitize the production process, and detect and develop improvements in the end to end flow (from sales to delivery), saving costs and increasing productivity. In addition, it will deliver a tested case study of the extensive application of process mining within an organization, and help perfect process analysis models, improvement proposals, and integration in real environments.

“This agreement will allow us to permanently improve our efficiency in all areas: we are not only talking about producing with less waste, errors, or unnecessary repetitions, but we will also improve our environmental impact by reducing the consumption of water, electricity, detergents… ” says Benigno Pereira, founder and managing director of Queizuar.

What is process mining?

Process mining is an emerging discipline that allows companies to improve their operations, increasing productivity and reducing costs by collecting information stored by computer systems and showing the real execution of their business processes. The data of the real life execution facilitates the identification of deviations from the planned processes, errors, waste or non-compliance with standards and procedures, which is vital in the food industry.

The Living Lab involves replicating in real time all the factory’s production flows and, in addition to analyzing efficiency and detecting execution problems, it enables testing with real data the different improvements that, based on its R&D, Inverbis applies to advance process mining as a science.

Among other lines of research, Inverbis works on generating and validating algorithms to detect the reason for deviations in production chains and the implementation of solutions in an environment that cannot stop at the moment of problem detection.

About Inverbis Analytics:
https://web.inverbisanalytics.com/

Inverbis Analytics is a startup in the field of artificial intelligence and big data created from research by CITIUS, the Singular Center for Research in Intelligent Technologies of the University of Santiago de Compostela. Among its reference shareholders are the University itself and UNIRISCO, the venture capital investment company specialized in bringing to the market scientific research from universities. Inverbis has been supported by the Galician Automotive Cluster through the BFAuto program, ENISA, the Ignicia Program of the Galician Innovation Agency (GAIN) and has recently obtained the support of the NEOTEC program of the CDTI.

About Queizuar:
https://www.queizuar.es/

QUEIZUAR S.L. is a company with more than 30 years experience in cheese production, heir to a family tradition that goes back generations. Its main goal has been to transition from a handcrafted production process to a modern system that, putting knowledge at the service of tradition, would allow to preserve the differential characteristics of the product and at the same time, meet all commercial safety and quality requirements. Continuous improvement, sustainability and the circular economy model are the framework in which we work, with the mission of providing our customers with a product that in addition to the quality they have come to expect, conveys the values of a production process based on efficiency and respect for the traditions and the environment.

Photo by Gerry Roarty on Unsplash

Read more…

The parallel activity dilemma in Process Mining

The parallel activity dilemma in Process Mining

Why commercial Process Mining does not do it (that much) One of the main advantages of discovery algorithms in process mining is that they are able to produce process models that abstractly represent how execution flows. This includes determining and modeling when...