ANALYSIS OF PRODUCTION AND OPERATIONS DECISIONS - BMEGT20MN15

The subject of Analysis of Production and Operations Decisions aims to teach and practice the analysis of complex production and service problems using a business simulation game, as well as solving case studies. The examined problems necessitate a series of solutions to the resource allocation tasks that often occur in management practice. The subject develops the students' ability to create independent models and formulate problems, as well as shows how complex decisions in the field of production and service management can be examined and supported with modern computer tools. With the help of the management simulation that accompanies the whole subject, the students directly apply their group decision-making skills and their previous knowledge of production and service management. The simulation game is evaluated using data envelopment analysis (DEA), which is also part of the semester curriculum. Thus, the learned evaluation and analysis method is also applied in practice.

1. Knows the basic methods of complex resource allocation problems.
2. Knows and understands the tools of mathematical modelling of the studied problems.
3. Understands the connections between the areas of corporate operation and production management.
4. Has confident methodological knowledge in the field of quantitative decision analysis, understands and understands the potential possibilities of the application of modern data analysis.

1. Able to formulate problems related to production and service processes verbally and analytically, to synthesize basic theories and practical aspects, to make rational arguments, ie to form and defend one's opinion during discussions in different fields of operational communication.
2. Able to plan the process of solving production and service problems and follow the path from problem recognition to solution.
3. In his professional vocabulary, he confidently uses the basic concepts of decision analysis, operations research and informatics, the professional language of the profession, and the elements of the special vocabulary based on them.
4. Able to interpret, evaluate, and use data related to production and services in performing design and analysis calculations.

1. Accepts that the possibility of improving certain company processes and their optimal operation can be determined by quantitative means.
2. Consciously represents the methods with which he / she works in his / her own profession and accepts the different methodological peculiarities of other disciplines.
3. It strives to make its decisions in consultation with the supervised staff and, where possible, in cooperation with them.
4. Has a comprehensive systems approach in the field of quantitative modelling.

1. Being able to perform and manage complex tasks in accordance with the professional expectations of a professional work community.
2. Independent, constructive and assertive in forms of cooperation inside and outside the institution.

Lectures; participation in a production simulation game that accompanies the entire semester; processing case studies inde-pendently and in group work.

• Koltai, T, Kalló N. Tatay V.: Termelési és szolgáltatási döntések elemzése, oktatási segédlet, 2017
• Szimulációs játék kézikönyv
• Egyéb, az oktatók által kiadott oktatási segédletek (https://edu.gtk.bme.hu)
• Koltai T.: Termelésmenedzsment, Typotex, 2006
• Koltai T.: Alkalmazhatók-e a termelésmenedzsment kvantitatív összefüggései a gyakorlatban, Harvard Business Manager (Magyar kiadás), 5(2), 52-59, 2003.
• Koltai T.: A kvantitatív összefüggések jelentősége a termelésmenedzsmentben, CEO magazin, 4(4), 11-14, 2003.
• Ragsdale, C. T.: Managerial Decision Modelling, Thomson, 2007.
• Lecture notes and slides uploaded to the Moodle page of the course (https://edu.gtk.bme.hu)
• Simulation game manual
• Ragsdale, C. T.: Managerial Decision Modelling, Thomson, 2007.
• Reid, R.D. & Sanders, N.R.: Operations Management: An Integrated Approach, 7th Edition, Wiley, 2020

The learning outcomes set out in point 2.2 are assessed during the examination period by a written examination

A. Detailed description of performance evaluations during the term: The result of the simulation game running during the semester is part of the grading of the subject. A maximum of 25 points can be reached based on the performance given in the game. A minimum of 10 points can be gained for the comple-tion of the game. The portion between 10 and 25 points is calculated proportionally based on the DEA efficiency score calculated from the results of the simulation game. For 100% efficiency you get an extra 15 points, for 0% efficiency you get an extra 0 points. The value between 0 and 15 points is given to the student as a percentage of the efficiency score. B. Performance evaluation during the examination period (exam): Written examination based on problem solving. Elements of the exam: 1. written performance evaluation: checking the theoretical background and practical application of the topics covered during the semester. The majority of the 75 points available in the exam can be obtained by solving the calculation examples (90%), a smaller proportion by answering the theoretical questions (10%).

• Participation in the simulation game is mandatory during the semester. As a result of the simulation game, a maximum of 25 points can be obtained, which is 25% of the subject's qualification.: 25

• written exam: 75%
• the result of the simulation game: 25%
• total: 100%

The condition for obtaining the signature is the successful completion of the simulation game.

According to the Code of Studies

Consulted with the Faculty Student Representative Committee, approved by the Vice Dean for Education, valid from: 04.10.2021.

To achieve the learning outcomes set out in section 2.2, the course consists of the following thematic blocks.