Research needs in large scale industrial systems
Applications of Large Scale Industrial Systems, Volume # 1 | Part# 1
Matti Paljakka; Olli Venta
Digital Object Identifier (DOI)
large-scale systems,decision support systems,models,standards
In today's industry, the requirements concerning the cost effectiveness of the production as well as end product quality are becoming even harder. Companies operating at real time in globalized business require agile production that quickly responds to changes in the business environment. The build-up, operation and maintenance of large scale industrial production systems require a whole network of experts of different domains. In setting up such a network, one must carefully design the roles of the actors in a manner that the network supports the overall performance of the system. Also the views through which each actor accesses the system must be designed to efficiently support his decision making. Recent research has made great advancement in data mining and information discovery in large sets of data. Also the modelling and simulation is slowly but surely being taken up in different phases of the plant life span. The standardization of plant life cycle data as well as on-line interfaces for the exchange of data and events has taken steps forward. Furthermore, mobile solutions and advanced visualization are entering the industry. All of this is surely helpful in managing large scale industrial systems. Often the question remains: what is the overall good performance of the system. What is now needed from the research is practical methods for selecting appropriate performance metrics and for implementing decision support systems for managing and controlling of the operative state in a large scale industrial system. The methods must take into account the network nature of the organization and the human-technology interaction of each actor in the network.
No references available