(441f) Waste Treatment Plant Model Based On Knowledge Management Technologies for Decision Making Support

Nowadays, it is important to provide systems capable of representing and considering the different elements involved in the enterprise decision making task, such as production, marketing, sales, human resources, logistics, safety and environment. In this area, knowledge management technologies have proved to be highly promising for improving information sharing and communication, enhancing the enterprise operation.

Waste treatment plants comprise several technologies, and treatment allocation decisions are usually taken based on company-specific selection criteria. Waste streams involving gas, liquid or solid effluents which contain contaminants originated from industrial activities must meet discharge constraints imposed by environmental regulations before being disposed of in the environment. Therefore, there is a large amount of data and information which has to be collected and organized, and the choice of the adequate option for an entire manufacturing site with hundreds of continuously changing effluents is highly challenging.

In this context, the use of an ontological model for representing a waste treatment plant has been detected as an opportunity for providing decision makers with new technologies to assess and evaluate the plant performance using information quality. This work aims at improving the information management based on a semantic representation of a waste treatment plant, namely its operational and logistics functions. As a result, more accurate information is provided to the optimization tools which will lead to better solutions based on the plant constraints.

In this work, the data which are introduced in the decision support systems are directly problem instances of the ontological model, whose dynamic values (those which are frequently updated) are read from different databases. What is more, an automatic order of the net of databases which many times are spread along the different hierarchical decision levels, is achieved since every database is adequately related to the corresponding part of the ontological model. Every relationship between the dynamic value, e.g. demand data property in the ontology, and its corresponding numeric value stored in the data base is easily programmed in Java language.

Therefore, the re-usability of an enterprise wide ontology representation for the enterprise waste management system is demonstrated. It stands for a decision-making support tool that defines and recognizes the various elements found throughout the hierarchy levels associated with waste management system and the related enterprise functions. As a result, this work allows improving the data communication from the transactional systems to analytical models. Overall, the main contribution of this work consists of providing greater efficiency in communication and coordination procedures in waste management systems.

The ontology has proved to provide decision-makers with improved data for the waste management related activities. Specifically, the ontology supports decision-making by streamlining information and data integration by an integrated and structured model that captures the activities carried out in the site. This model is intended to promote transversal process-oriented management to enable crossover among the different functional silos in which businesses have typically been structured. Such structures can recognize the existing trade-offs and the impacts of the available alternatives at the various information aggregation levels. Thus, by returning the decision-making/optimization model according to the current enterprise status, non-significant effects can be discarded. Additionally, the ontological model optimizes the way in which the databases are distributed along the informatics structure of the enterprise. As a result, databases can be well located so that their data can easily be accessed and transformed into valuable information.

Specifically, this work represents a step towards supporting the integration of various software tools applicable to the management and exploitation of plant data. As a result, the entire process management structure is enhanced to aid the automatic design and operation of more waste management systems based on the exploitation of information quality.

Acknowledgements

Authors would like to acknowledge to the Spanish Ministerio de Economía y Competitividad and the European Regional Development Fund for the support by projects EHMAN (DPI2009-09386) and SIGERA (DPI2012-37154-C02-01) and to the Centro de Investigacion en Matematicas (CIMAT) from Mexico.