Business Process Modeling and Optimization

Subject	Business Process Modeling and Optimization
Semester	4th semester (spring)
Type	Required (area of study: Management and Law)
ECTS	6 ECTS
Study programme:	Business studies (Master)
Primary language:	Slovene

Introduction
The course is taught in Slovenian or English and is a compulsory course in the Master's degree programme in Business Studies. The course can be delivered in the classroom or via the online application ZOOM, depending on the applicable guidelines of the Faculty of Law and Business Studies.
The course provides an introduction to the understanding of business processes and some of the basic methods for establishing, planning, controlling and quality of business processes. The course is sourced from "Manufacturing Systems Analysis" by Stanley Gershwin of the Massachusetts Institute of Technology. The course includes an online chat room where students can ask questions and answer questions related to the subject matter.
Recorded (approx. 15-minute) explanations of some of the material and lecture transparencies have been added to the material. At the end, students prepare a roadmap of the selected business processes using a fictitious company as an example.

Preconditions
Students should understand the basic mathematical concepts of stochastic processes, optimisation and differential equations, and the basic statistical concepts of probability distributions. These prerequisites are standard material for university studies at any Slovenian or international faculty (business school). Students must have sufficient knowledge of English to be able to use the material independently.

Goals

1. To learn about some of the important issues in the design and implementation of production system processes.
2. Explain some important dimensions of system performance.
3. Demonstrate the importance of random events with the power to weaken the system.
4. To give some intuition about the behaviour of manufacturing systems.
5. To learn to understand the use of mathematics and statistics in the description and analysis of manufacturing processes.
6. To test knowledge of the operation of business processes by means of a practical example.

Competencies

1. To develop the link between theory and practice in the use of business process analysis methods.
2. Developing soft (intuitive) and hard (analytical/mathematical) approaches to business operations
3. Developing methodological rigour in the assessment of business processes and the perception of business processes as necessarily at least partly stochastic
4. Developing intuition in establishing the business functions and risk factors in the operations of a specific (study) firm
5. To develop an awareness of the importance of optimising business operations, not only in the case of Markov production
6. Building confidence in the engineering profession in the management of companies and raising awareness of the importance of cooperation between different departments in a company with the aim of successfully managing business processes

Syllabus
1 Introductory lectures
2 Probability and random variables -- basic concepts
  2.1 Binomial distribution
  2.2 Geometric distribution
  2.3 Exponential distribution
3 Markov chains and processes
  3.1 A non-functioning machine
  3.2 M/M/1 queues
  3.3 Inventory management
4 Project work (special instructions)
 
Teaching and learning activities

• Lectures (online or face-to-face) and
• Independent and individual work by students

Metode (načini) dela

• Interpretation
• Seminar work
• Interview/debate
• Problem solving

Evaluation systems and criteria
The assessment consists of three elements: 1) Written exam (45/100), 2) Active participation (10/100), 3) Seminar/project work in a virtual company (45/100). The written examination is conducted during the regular examination period. The production of a project is a prerequisite for taking the written examination. Submission of the project work: by e-mail or in a special place on the online cloud by the beginning of the examination period.

Teaching and learning material

• Steinbacher, M. 2022. Zapiski predavanj.
• Gershwin, S. 2006. Stochastic Modeling of Manufacturing Systems. Springer.
• Web portal: https://ocw.mit.edu/courses/mechanical-engineering/2-852-manufacturing-systems-analysis-spring-2010/. Students are reminded of the rules on the use of the material at: https://ocw.mit.edu/terms.
• Lecture handouts with summaries of the core content, supplementary materials for project work and other study materials.

Office hours

• by email
• regular weekly consultations
• by arrangement