User:Smouton/sandbox

Proposed title: Intelligent Integrated Manufacturing

Article should begin by a short definition of I2M here.

New technologies are among the most important ways of covering the technological gap required in process optimisation and increased competitiveness. Where conventional techniques are mature and robust enough to guarantee stable performance, Integrated Intelligent Manufacturing (I2M) technology should contribute to developing more flexible, cost optimal and environmental friendly production processes. One important topic here is the complete and integrated process and plant automation as well the inter-process logistic of the complete processing chain to gain notable improvements in product accuracy, yield and process reliability. Furthermore different decision support tools, quality assurance techniques, plant condition information and methods to integrate the engineers/operators knowledge are important to improve the overall performance of steel metal steel production. For all these activities it is essential to have the necessary input information with suitable accuracy at the correct time at the right place. Therefore data acquisition systems sensors to gather the necessary data and powerful IT solutions to handle their results are absolutely essential. All these aspects together define the “Integrated Intelligent Manufacturing (I2M)” paradigm. Among the different R&D and innovation topics covered by the above subject of I2M, the following are particularly highlighted:

The above description is furthermore fully in line with the aims of the “Factories of the Future (FoF)” initiative of the 7th and 8th framework of the European Union.
 * Integrated automation solutions based on the information related to single processes as well as to complete process chains taking into account all aspects of automation (e.g. monitoring, diagnosis, assistance systems, process control, plant condition control, process supervision, logistics, etc.) by using the newest available techniques in all these fields (model predictive, robust or iterative learning control; self learning technologies; rule based or knowledge based decision support; robust optimisation techniques; etc.)
 * Implementation of integrated quality control systems allowing the incorporation of factory wide systems to control the evolution and influences in terms of quality through the different stages of the process chain. This implies the application of information technology (new IT paradigms) to allow better linking of process operations and plant logistics to give production flexibility, guarantee product quality and meet end user/customer requirements for ‘just-in-time’ order delivery. The full implementation of these systems is closely linked to the previously mentioned development of models and sensors.
 * The total integration of environmental aspects like energy consumption, CO2-emission etc. into all of the above systems as additional constraints to optimise finally the overall performance of the metal steel production in terms of production costs, product quality, lead time and environmental footprint.
 * The integration of plant condition aspects in order to optimize the overall plant availability as well as to support predictive maintenance strategies.
 * Universal solutions for handling of all the above information, methods to improve their reliability, techniques to assign them to the products or the products length, ways to explain their meaning to all applications which use them, tools to analyse these data on- and off-line by using newest technologies like Data Mining, etc.
 * The complete integrated modelling of single processes and production lines by new and accurate mathematical models. Three approaches should be followed here: analytical, data based and hybrid modelling. The modelling should be extended to all levels of automation, including scheduling and management systems as well as decision making processes.
 * Implementation of new functions in the measurement (reliable, fast, accurate, non-contact, soft sensors) and monitoring chain along the production processes for plant/process variables and product parameters in combination with their complete integration in the automation environment of the plants.
 * The full integration of all the above technologies in a user friendly way (improved HMIs) and at the same time improving their flexibility (mobile data).