Konetekniikka - Mechanical Engineering

The content of the course consists of nine main themes as follows: 1. Differences between information management and knowledge management. 2. Social media and leadership and management: challenges and possibilities related to different social media channels. 3. Leadership vs. management including the following issues: different leadership styles (coaching, visionary, servant, autocratic, Laissez-faire or hands-off, democratic or participative, pacesetter, transformational, transactional and bureaucratic leadership). 4. Principles for understanding different cultural backgrounds. 5. Leadership in line and matrix organizations. 6. Change management vs. change leadership. 7. Leadership and management in digital networking environments in engineering. 8. How to recognize and handle stress including the following issues: Stressful situations in different leadership and management positions, signs of stress, ways to relief the recognized stress. 9. The future trends of modern leadership and management in engineering.  10. Innovation leadership and innovation management.

Learning outcomes:  The learning outcomes of this course are mostly related to support research activities in the field of mechanical engineering. The main learning outcomes are as follows: - Criteria to evaluate the scientific contribution of research - Scientific research projects especially in mechanical engineering - Principles of qualitative and quantitative analysis - Reliability aspects and utilization of triangulation especially for research work in the field of mechanical engineering - Viewpoints on how to illustrate the results of quantitative analysis - Different means to carry out literature reviews, interviews and surveys - Utilization of silent knowledge - Contents and structures of research plans and reports s based on the IMRAD principle and C.A.R.S. model 

Decision making is a reoccurring topic in engineering. The accurate control of mechatronic actuators requires split-second decisions on control signals to ensure sufficient performance. Autonomous systems like service robots and autonomous cars need to swiftly decide on plans, like action sequences or planned trajectories, based on information from sensors, maps, and users. Similarly, design engineers occupied with designing mechanical and dynamical components of systems are themselves faced with many decisions on the way from an empty design sheet to a finished product. Modern engineering design seeks to automate and formalize at least parts of the design process to arrive at better designs more quickly, meeting future goals not only regarding key performance metrics but also regarding sustainability, e.g., through better energy efficiency, easier recyclability, and reduced material usage. One common way to formally deal with the mentioned types of decision-making problems is mathematical optimization.When formulated appropriately, solutions of optimization problems, usually obtained with numerical algorithms, represent good decisions that are optimal regarding formalized criteria. Following this background and understanding of optimization in mechanics and dynamics, the course covers the following content: Formulation of optimization problems Classification of optimization problems Optimization criteria Sensitivity analysis, including automatic differentiation Optimality criteria Optimization algorithms for constrained and unconstrained convex problems Global optimization strategies for non-convex problems Multicriteria optimization Optimal control based on models from mechanics and dynamics Various practical examples from design and control in mechanics and dynamics for formulating and/or solving optimization problems.

This course explores state-of-the-art industrial Mechatronics, with a focus on: AI in Mechatronics – AI-driven automation, machine learning for predictive maintenance, and AI-enhanced control. Smart Sensors and Actuators – Digital hydraulics, intelligent sensing, and sensor fusion for real-time control. Human-Robot Collaboration – Safety, efficiency, and applications in manufacturing, logistics, and service robotics. Industrial IoT (IIoT) – Connected automation, cloud-based monitoring, and smart factory case studies.

The course deals with the following topics: - Design and analysis procedure of industrial steel structures based on available load information, durability requirements and main boundary conditions given by mechanical system - Use of practical design tools (analytical and numerical) and optimization approaches to design energy efficient constructions - Working as a member of design group, consisting of design/analysis and fabrication experts - Fabrication plans, particularly welding process specifications (WPSs) for a structure, or a complete structural member of it - Methods to take into consideration the available workshop facilities when choosing fabrication processes and evaluating fabrication costs. - Practical interactive process between design and fabrication to find a compromising solution considering strength requirements and fabrication costs of critical structural details. - Documentation of design and fabrication plan. The course module provides knowledge about the design, analysis and fabrication process of demanding structural applications needed in Power-to-X solutions.

The course deals with the following topics: analytical and numerical structural analyses of studied welded joint manufacturing and welding preparation of experimentally studied joints execution the applied gas metal arc welding (GMAW) process in laboratory performing metallurgical investigations (macro-micro level analyses, hardness measurements, etc.) for the studied welded joints conducting measurement procedures and analyses on the geometrical parameters, residual stresses and strains (e.g. strain gages and digital image correlation systems), as well as deformations and loads in the structure carrying out capacity tests (static and fatigue) and analyzing and reporting results, systematically reporting and presenting experimental research work The course module provides knowledge about the experimental methods and studies to investigate the performance of structural components used in Power-to-X applications.

Manufacturing processes in a production environment context. Key concepts using in product design Human-centered design guidelines and methods Human-centered problem solving Related knowledge of physical, cognitive, and organizational ergonomics Human factors engineering Manufacturing technologies, product areas, production material and technical production parameters. Human product interaction Usability design Human-centered design guidelines and methods Information visualization Team work User studies Design methodology and product development Evaluation and analysis of methods and creative processes Research in design

· Related knowledge of physical, cognitive and organizational ergonomics · Human interaction and influence on the design of new products · User experience and usability in design · Ergonomic evaluation methods on real cases · Environmental, psychological and physical factors · Human factors engineering

Introduction to processing technology and overview of manufacturing processes. Usable material forms: fibres and fabrics. Fundamentals of laminate construction. Matrix resins: thermoplastic polymers vs. thermosets. Manufacturing methods: lay-up processes, filament winding, pultrusion, transfer moulding, compression moulding, rotational moulding, injection moulding and extrusion. Composite industry overview: applications for composites, history and current technologies. Applications in energy systems, aeronautical industry, automotive industry, marine industry, and construction industry. Product safety: characterization of material properties. Company cooperation: Technological examples and topics from the companies in the lectures. Use of AI applications: The use of AI applications to support learning is allowed in the course (e.g. for outlining the content of seminar paper or improving grammar in seminar paper) in accordance with LUT's AI policy. The use of AI must be documented in the course assignments.

The course will cover the following topics. What are recyclable materials?  Waste policy and waste hierarchy in EU and globally. EoW legislation.  Pre-treatment and sorting methods for recyclable materials.  Potential manufacturing and production methods for recycled materials. Recycled end products. Company cooperation Technological examples and topics from the companies in the lectures. Use of AI applications The use of AI applications to support learning is allowed in the course (e.g. improving grammar in the seminar work), in accordance to the LUT AI policy. The use of AI must be documented in the course tasks.

During the course, the student will become familiar with scientific research. This comprises: · Planning scientific research and finding suitable publication channels for research work, considering student-specific content · conducting extensive literature reviews supporting scientific work · performing metallurgical investigations (macro- and micro-level analyses, hardness measurements, etc.) for in the studied field · carrying out mechanical testing, and analyzing and reporting experimental results · peer-support and problem solving on research topics · presenting research topics in clear and understandable way to scientific community. The course module provides knowledge about the experimental methods and studies to investigate the performance of structural components used in Power-to-X applications.

Ekvivalentit voimasysteemit, staattisen voiman ja voimaparin aiheuttama momentti, partikkelin ja jäykän kappaleen tasapaino 2D-tilanteessa, voima ja kiihtyvyys, työ ja energia, impulssi ja liikemäärä. Törmäykset, impulssikuormat, 1. vapausasteen värähtelijä, pakkovärähtely, vaimennettu värähtely. Pähkinänkuoressa: 2D-statiikkaa ja dynamiikkaa partikkelille ja jäykälle kappaleelle.

Ekvivalentit voimasysteemit, staattisen voiman ja voimaparin aiheuttama momentti, partikkelin ja jäykän kappaleen tasapaino 2D-tilanteessa, voima ja kiihtyvyys, työ ja energia, impulssi ja liikemäärä. Törmäykset, impulssikuormat, 1. vapausasteen värähtelijä, pakkovärähtely, vaimennettu värähtely. Pähkinänkuoressa: 2D-statiikkaa ja dynamiikkaa partikkelille ja jäykälle kappaleelle.

Samaan pisteeseen vaikuttavien voimien yhdistäminen, voiman staattinen momentti, voimaparin momentti, partikkelin ja jäykän kappaleen tasapainoehdot, rakenteen sisäiset rasitukset, partikkelin kinematiikka, voimayhtälöiden, energiaperiaatteen ja impulssin sekä liikemäärän periaatteen soveltaminen partikkeleille. Yleisesti: Differentiaalilaskennan ja vektorianalyysin käyttö opintojakson aihepiireissä.

The course deals with the following topics: - Design criteria and criticality of different failure modes based on the operating conditions - Recognition of static and cyclic loads, and determination of cyclic loads as per the equivalent stress concept - Categorization of load and stress components - Load-based categorization of different joint types - Design and analyses of welds and welded joints under static and fatigue load actions - Stability of plates and beams, standardized methods for categorizing slenderness of beam profiles The course module provides knowledge about the design, fabrication and analysis of demanding structural applications that can be used in the Power-to-X solutions.

The course deals with the following topics: - Design principals to avoid fatigue failure of mechanical engineering components and structures - Introduction to fatigue in micro and macro scale, deformation of structural materials, stress concentrations and fracture mechanics  - Design of structures based on stress-life approach, strain-life approach and linear elastic fracture mechanics. The course module provides knowledge about the use of fatigue design methodologies that provides deep understanding to assess the structural life cycle of mechanical components used in Power-to-X applications.

Course comprises of 10 lecture topics: 1. Introduction 2. Sensors and situational awareness 3. Vehicle simulation - part 1 - dynamics 4. Vehicle simulation - part 2 - sensors integration 5. Vehicle simulation - part 3 - predictive control 6. Vehicle simulation - part 4 - high-level control and navigation 7. Autonomous mobility infrastructure 8. External lecture by invited industry or academic specialist - Topic and lecturer will be announced on one of the first lectures in the course 9. Cyber security 10. Cyber security in connected cars: threats, attacks, and protection

Numerical modeling techniques for correct and efficient programming using Matlab. Sparse and dense matrix computations, debugging and profiling of the code. Common code mistakes and good practices. Numerical solution of the equations of motion of rotating systems. Eigenvalue analysis of linearized systems. Numerical integration of the ordinary differential equations for analysis of nonlinear systems. Practical modeling and analysis techniques using commercial finite element software.

Best practices for writing correct and efficient code in MATLAB, including debugging techniques. Identification of common coding mistakes and strategies for improvement. Numerical solutions for the equations of motion in vibrating and multibody systems. Numerical integration of ordinary differential equations (ODEs) and differential-algebraic equations (DAEs). Explicit and implicit integration methods, including constraint stabilization techniques. The Newton-Raphson method for solving nonlinear systems of equations. Numerical methods for solving partial differential equations (PDEs) relevant to mechanics. Introduction to unit testing for verifying computational implementations.

Principles of multibody dynamics, modelling of actuators, coupled simulation. Use of the concept of virtual work. Constraint equations and Lagrangian multipliers. Inertia of rigid bodies. Modelling of hydraulic components. Numerical integration of the equation of motion. Individual utilisation of simulation software, including the principles of how to apply previously mentioned mathematical theories to handling and solving abstract and multidisciplinary problems. The course module supports the following UN Sustainable Development Goals: #9 Industry, Innovation and Infrastructure.