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Decision-making process on field technology for process management

Tekijä: Koskinen, Pentti
Organisaatiot: University of Oulu, Faculty of Technology, Department of Electrical Engineering
Aineistotyyppi: e-kirja
URI: Kokoteksti (PDF, 2.1 MB)
Pysyvä osoite: http://urn.fi/urn:isbn:9514257855
Kieli: englanti
Julkaistu: 2000
Julkaisuaika: 2000-10-16
Opinnäytteen tyyppi: Väitöskirja
Väitöstiedote: Academic Dissertation to be presented with the assent of the Faculty of Technology, University of Oulu, for public discussion in Kuusamonsali (Auditorium YB 210), Linnanmaa, on December 2nd, 2000, at 12 noon.
Tarkastaja(t): Doctor Sakari Kauppinen
Prof.Dr. Hartwig U. Steusloff
Kuvaus:

Abstract

Intelligent field technology is being developed for the management of industrial processes, but its development and diffusion have met with problems. This research looks at the problem area from the perspective of industrial decision-makers and end users. The lowest level of process management consists of various electrical, pneumatic and hydraulic devices, using analog and digital signals. In this research the term 'field technology' refers to instrumentation and electrical devices, the communication between them, alarm and registration devices, programs, functions and process management methods. Important concepts in this connection are distribution, availability performance, usability, feasibility and degree of automation.

Decision-making and hermeneutical methodologies have been used as research strategies. The leading idea is to provide support to industrial decision-makers and end users involved in the design and planning of processes, field technology and management systems. The research strategy is applied in all parts of the research: methods, historical review, decision-making support model and criteria, and when studying the diffusion of innovations.

The objective is to experimentally verify the decision-making models. This was accomplished by means of multiple-choice questionnaires, example and case process surveys, and by collecting information on intelligent field technology. The target group of the research consisted of 50 decision-makers and end users from 20 factories, and the response percentage varied from 28% to 47%. The study of the example and case processes contains contributions from 13 key persons from the factories. Field technology knowledge has been obtained from a number of experts and sources.

The results have been employed to verify the current multivariable decision-making model and its technological and economic subcriteria and decision-making criteria (1), as well as the expanded multivariable decision-making model based on the features of intelligent field technology (2). The most significant parameters of the example processes are described (3). The typical characteristics, operations, input and output materials of the case processes and their parameters are examined and assessed (4). A proposal for intelligent field technology solutions will also be made (5).

The decision-making support model is an excellent tool in situations involving technological changes. The current set of decision-making criteria will have to change and expand due to the concepts, operations and changes introduced by new, intelligent field technology. Changes will occur in the communication protocol interfaces, in the data processing of field devices, in diagnostic operations and operation management. Suitable decision-making tools include development and decision databases, lifelong learning, human and electronic information networks, the decision-making support model, and benchmarking. In the future, investments will focus on the acquisition and maintenance of field technology. Intelligent field technology is more expensive, and thus automation design requires more economic and human resources during the diffusion phase; its economic benefits will become more apparent when it gains more ground and the users' skills and expertise increase. Industrial enterprises must actively seek to promote the diffusion of innovations. The current research has also brought up numerous topics that would merit further research.

Sarja: Acta Universitatis Ouluensis. Series C, Technica (152)
ISSN: 0355-3213
ISSN-E: 1796-2226
ISBN: 951-42-5785-5
ISBN Print: 951-42-5784-7
Numero: 152
Aiheet: decision-making criteria
decision-making support model
diffusion
multivariable decision-making
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