Learning objectives
Knowledge and understanding:
at the end of the course, students will have acquired the basic knowledge about the structure and functioning of a simulator, in terms of: analysis of the context to by reproduced; statistical analysis of the process data; tools available to develop a simulation model for the process analyzed; analysis of the data obtained by the simulation; optimization of operating leverages, to improve the performance of the process.
Applying knowledge and understanding:
students will be able to develop a process simulator, both in the logistic and production context, starting from the scenario to be analysed, by choosing the tool that better reproduces the process studied, identifying performance indices and operation leverages on which to act through "what if" analyses, to optimize the process or propose alternative process configurations.
Making judgements:
supported by the results of the simulation campaigns, students will be able to evaluate the impact of design decisions and operational leverages on the performance of complex productive and logistic systems.
Communication skills:
students should acquire the specific vocabulary related to simulation. It is expected that, at the end of the course, students will be able to communicate the main contents of the course both orally, in writing and through the implementation of ad hoc simulators, either supported by “general purpose” softwares or dedicated tools.
Learning skills:
Students who have attended the course will be able to deepen their knowledge in the field of process simulation, by consulting specialized texts, or journal papers, or other sources, as well as new software packages (both "general purpose" or dedicated), also outside the topics covered in class.
Prerequisites
There are no compulsory prerequisites
Course unit content
The aim of this class is to provide the basis knowledge related to the main aspects of simulation studies in the field of logistics and manufacturing systems, including modeling, simulation languages, validation and output data analysis
Full programme
Basic Simulation Modeling (the nature of simulation; system, modes and simulation; discrete event simulation, distributed simulation, steps in a simulation study, other types of simulation; advantages, disadvantages and pitfall of simulation).
Review of basic probability and statistics.
Building valid and credible simulation models.
Selecting input probability distributions.
Output data analysis for a single system.
Comparing alternative system configuration.
Experimental design and optimization. Production process simulations, Production system simulations.
Inventory management by a simulation approach
Advanced utilization of MS Excel as general purpose tool for simulation
Utilization of Simul8 as a simulation tool for production systems
Bibliography
The notes of the lectures and exercises, and all the supporting material (drawings, plant schemes, Excel spreadsheets, media) are available to students and shared in a DropBox folder. To be invited please send a mail to the professor roberto.montanari@unipr.it including "Shared folder IM Drive" in the Object field.
In addition to the shared material, the student can personally study some of the topics discussed during the course in the following books:
• A.M. Law and W.D. Kelton, Simulation modeling & analysis, McGraw-Hill, Inc.
Didattica e tecnologie digitali. Metodologie, strumenti, percorsi. Antonio Marzano. Editore: Pensa Multimedia
La didattica laboratoriale. Manuale di buone pratiche. Cosa fare, come fare. Tommaso Montefusco. Editore: Edizioni Dal Sud
Teaching methods
The course counts 6 CFUs (one CFU, University Credits equals one ECTS credit and represents the workload of a student during educational activities aimed at passing the exams), which corresponds to 48 hours of lectures. The didactic activities are composed of frontal lessons in informatic LAB alternating with exercises. During the frontal lessons, the course topics are proposed from the theoretical and design point of view.
During classroom exercises students can use computers of the informatic LAB, and they will apply theoretical knowledge to an exercise, a real case study, or a project.
If conditions are favorable, seminars are held by managers of multinational corporations who report concrete experiences in real case studies.
The slides and notes used to support the lessons will be uploaded to the Elly Platform and a shared folder on DropBox. To download the slides from Elly is required to enroll in the online course, while to be added to the share folder you need to send an email to the teacher roberto.montanari@unipr.it as the object "Shared folder SSP".
Notes, slides, spreadsheets, tables, and all shared material are part of the didactic material. For non-attending students, it is important to stay up-to-date on the course through the Elly platform, the only communication tool used for direct teacher / student contact.
Assessment methods and criteria
Verification of the knowledge takes place through:
- a written test based on DOE exercise. It is a barrier for the verification.
- Simulation of production system on PC (3h). The simulation usually consists of 5/10 questions (the same weight = 1). The final vote is calculated by assigning a mark in the range 0-30 for each question and then performing the weighted average of the individual evaluations, with final ceiling to the next unit; the test is exceeded if it reaches a score of at least 18 points. “30 cum laude” is given to students who achieve the highest score on each item and use precise vocabulary.
Other information
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2030 agenda goals for sustainable development
