Integration of the decision making of the tactico-operational levels for the improvement of the production system efficiency in environments industry 4.0 (NIOTOME)

This project proposes adapting the instruments available in the tactical and operational level of the Operations Planning and Control System (OPCS) so that they are able to take advantage of information from their environment to provide solutions that are more adjusted to the reality of each moment, without being instability, improving the long-term efficiency of the productive system.

Nowadays, thetechnologies that facilitate these processes of change in industrial companies are located under the concept of “Industry 4.0”. Currently there are a number of shortcomings in the OPCS as the tactical and operational levels must have decisional independence, as well as a high degree of coordination (control) based on the exchange (improvement of the flow) of accurate information (simplification) , of specific methodologies and algorithms for the improvement and selection of the proposals (intelligent decisions).

Information must be put on value and its obsolescence (agile). The data must be treated and converted into relevant information that must reach all decisional levels for effective decision making. The simple updating of values of the models with the data already available, the elaboration of values based on automatic learning systems, or the transformation of the restrictions or objectives of the models under the tutelage of a manager that establishes the most appropriate moment to do it. These are aspects that should be considered.

The main objectives of the proposal are:

1. Create a conceptual proposal that effectively extends the OPCS based on an architecture, an implementation methodology, some models and some (intelligent) algorithms, that:

• Improve the consistency of OPCS decisions through an extension of the decision process that closes the tactical-operational loop (Flow from operative to tactical).
• Increase coordination to improve efficiency in production plans and programs.
• Improve the reactivity of the decision makers and increase the ability to adapt.
• Allow continuous learning of the decision process.
• That is replicable and applicable to multiple types of companies.

2. Create a computer tool that supports the proposed decision process and helps decision making by facilitating the understanding of the partial problems (decisional levels) and global (tactical-operational set) and reproducing the decision logic of an expert, being:

• Easily integrable with current systems, especially with industry 4.0 technologies
• Respectful of current business processes.
• Easy to implement, simple to manage and interact.