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Syllabus for

Academic year
IBS092 - Decision support systems in industrial management
 
Owner: TIEKA
5,0 Credits (ECTS 7,5)
Grading: TH - Five, Four, Three, Not passed
Level: A
Department: 45 - TECHNOLOGY MANAGEMENT AND ECONOMICS


Teaching language: English

Course module   Credit distribution   Examination dates
Sp1 Sp2 Sp3 Sp4 No Sp
0104 Examination 5,0 c Grading: TH   5,0 c   Contact examiner,  Contact examiner,  Contact examiner

In programs

IQMAS MSc PROGR IN QUALITY TECHNOLOGY AND MANAGEMENT, Year 1 (elective)
IOMAS MSc PROGR IN PRODUCTION AND OPERATIONS MANAGEMENT, Year 1 (elective)
TIEKA INDUSTRIAL ENGINEERING AND MANAGEMENT, Year 4 (elective)

Examiner:

Professor  Hans Björnsson


Replaces

IBS091   Decision support systems in industrial management


Eligibility:

For single subject courses within Chalmers programmes the same eligibility requirements apply, as to the programme(s) that the course is part of.

Course specific prerequisites

TDA140 Datoranvändning och programmering (Computer Use and Programming),
IBS130 Simulation for Production and Corporate Planning or equivalent.

Aim

This course focuses on computerized decision support systems, emphasizing a knowledge-based perspective. With the relentless advances in the technology and economics of computers, we are rapidly reaching the point where a manager s success depends on his or her understanding of DSS possibilities and skill in DSS application. The course will provide a comprehensive understanding of DSS possibilities and impart practical DSS development and usage skills.

Content

This course covers the tools, techniques, and theory of DSS and how they can be used to improve the quality of management decisions. It teaches students how MIS managers design systems that allow: easy access to information, the ability to easily merge information from multiple sources, and creating models for analyzing the information. The course examines decision making in general, the translation of knowledge about decision making into a DSS model, and the structure of a DSS.

Beginning with an introductory look into the nature of human decision making, topics covered in class will include: basic structure and components of decision support systems, data-warehousing and related analytical tools, modeling methods to aid in decision making, utilization of web-related and collaborative technologies, knowledge-based systems and artificial intelligence methods to support decision making, including data mining. Theoretical discussions on these topics will be supplemented through hands-on exercises with various software tools.

Theoretical underpinnings of DSS are provided through lectures but the major part of the course is concerned with practical applications using tools and technology currently available. Several tools commonly used in real business situations will be used.

Organisation

The course consists of lectures, case studies, seminars, and computer labs.

Literature

A special reader will be distributed at the first class meeting. Other material will be distributed later. Internet links will be referred to and students are encouraged to search for material on their own

Examination

Performance in the course is assessed through project assignments and a written examination. The final grade for each student is a function of the results from different exams, as follows:
40% weight for Written Exam
60% weight for Project assignments (5)


Page manager Published: Mon 28 Nov 2016.