86476 - Industrial Plants Design

Learning outcomes

Knowledge and comprehension of the course contents in relation to the production system design.

Skills and capabilities in the application of the previously mentioned contents to real complex industrial cases where both the human and the machine components are present.

Expertise in the evaluation of the profitability of an industrial investment

Course contents

Requirements/Prior knowledge

The course does not require specific prerequisites except for the know-how acquired by the students during the bachelor degree required.

1. FEASIBILITY STUDY of INDUSTRIAL INVESTMENT (10hs)

• Feasibility study concept

• Relevance of product market analysis

• Market surveys: short, medium, long period

• Market demand components: trend, conjuncture, seasonality and random

• Survey product demand sampling method

2. PRODUCTION PLANT DESIGN (25hs)

• Product-Quantity analysis and industrial layouts concepts

• Main technological plants and others facilities

• Design of production systems (flow shops and job shops)

• Time influence on costs and amortization

• Characteristic curve and economic value of an industrial equipment

• Cell production design

• Collaborative Robot-machine systems

3. PROFITABILITY ANALYSIS (5hs)

• Cost classification and cost-return analysis

• Cash flows and actualization

• Fiscal amortization, methods for the profitability analysis of an industrial investments (NPV, TIR, Payback)

4. PROJECT WORK (20h)

• Project work in groups of 3/4 people focused on the design of a plant for the production of vehicles starting from a physical scale model.

Readings/Bibliography

• S.Heragu, Facilities Design, CRC Press, 2008, III Ed.
• Readings suggested directly by teacher (available on virtual learning platform platform)

Teaching methods

The course is organized in frontal lectures in which the basic elements of the various parts of the program are presented. Many lessons are devoted to the resolution of exercises and specific problems follow theoretical presentations of each topic. That underlines the applied nature of the discipline and aims to learn the method, i.e. the ability to translate in mathematical language a concrete problem to determine its solution then applicable in industrial realities.

Assessment methods

Learning assessment is carried out through the development of a project work dedicated to the sizing of a production system aimed at assembling a real vehicle. Through this activity, students will be able to put into practice the methodologies, tools, and knowledge acquired during the course.

Project works may be developed in groups, with a maximum of 3 people, and will be discussed in class at the end of the lectures.

Students will pass the exam if they demonstrate mastery and operational ability in relation to the key concepts presented in the course, with particular reference to the design criteria and feasibility assessment of an industrial plant. A higher score will be awarded to students who demonstrate that they have understood and are able to use all the course contents, showing the ability to establish connections between the different parts of the programme and to solve complex problems requiring an integrated approach to the various techniques discussed during the lectures.

STUDENTS WITH SLD OR TEMPORARY OR PERMANENT DISABILITIES

Students are advised to contact the relevant University office in good time (https://site.unibo.it/studenti-con-disabilita-e-dsa/it ). The office will propose any necessary adjustments to the students concerned; such adjustments must in any case be submitted to the lecturer for approval at least 15 days in advance. The lecturer will assess their appropriateness also in relation to the learning objectives of the course.

UNIVERSITY CODE OF ETHICS

In accordance with the University Code of Ethics, students are reminded to behave with the utmost integrity. Any activity aimed at improperly altering the outcome of assessments is prohibited, including, for example, cheating, plagiarism, accessing online teaching resources, or using unauthorized AI tools. In particular, students are informed that the mere possession of unauthorized devices or materials during the assessment will result in the immediate annulment of the assignment and reporting to the competent offices.

Conduct that violates this prohibition may lead to disciplinary proceedings or, where criminally relevant, reports to the competent authorities. In the latter case, the students involved may risk being subject to criminal proceedings.

USE OF GENERATIVE ARTIFICIAL INTELLIGENCE

With regard to learning assessment, limited, non-substantial use of AI is permitted for support activities, provided that it is explicitly and accurately declared in the final report. Such support activities may include summarization and the development of mechanical calculations once the problem has been properly set up. Substantial use of AI for carrying out parts of the assessment is not permitted.

 

Teaching tools

During the course, business visits and / or business testimonies are organized in the classroom to understand and discuss the problems related to the maintenance of the production systems most noticeable in industrial realities and consequently to understand the role of the techniques known during the lectures.

USE OF GENERATIVE ARTIFICIAL INTELLIGENCE

AI can be a useful tool to support individual study, assisting students with further exploration of topics, content summarization, and self-assessment activities.

Office hours

See the website of Alberto Regattieri