Konetekniikka - Mechanical Engineering

This course provides an in-depth exploration of advanced topics in finite element analysis (FEA) for solid and structural mechanics. It builds upon fundamental FE principles and extends them to more complex engineering problems. The course covers both theoretical foundations and practical applications through computational exercises using MATLAB and commercial FE software. Topics can cover, but are not limited to: - Introduction to continuum mechanics: Fundamental concepts, stress and strain tensors, constitutive modeling. - Linear and nonlinear finite element methods: Governing equations, solution strategies, and computational challenges in linear and nonlinear FEM. - Material modeling: Elastic, plastic, and viscoelastic material models; hyperelasticity; anisotropic materials; implementation in FEM. - Rigid-flexible body coupling: Interaction between rigid and deformable structures, numerical methods for coupled dynamics, and applications in multibody dynamics, vehicle dynamics, and biomechanics. - Linear thermoelasticity: Finite element formulation for coupled thermal and mechanical problems, steady-state and transient analyses. - Model reduction techniques in FEM: Substructuring methods, modal reduction and reduced-order modeling for computational efficiency. - Parameter identification and optimization in FEM: Inverse methods for material and structural parameter estimation, optimization techniques for model calibration, and uncertainty quantification. - Failure mechanics: Analysis of different failure modes in engineering, including ductile and brittle fracture, buckling, fatigue, within the FEM framework. - Contact mechanics in FEM: Formulation of contact problems, penalty and Lagrange multiplier methods, numerical implementation. The course module provides knowledge about the use of numerical (finite element) methods for analyzing and designing structures for Power-to-X applications.

The course starts with one or multiple initial physical sessions, introducing the goals of the course, the depth of tasks expected, and the project scope. Students are partitioned into groups by the teachers based on the results of a questionnaire assessing their skills and interests.  Automation problems tackled are either proposed by the teachers, by partner companies, or suggested by students, subject to instructor approval.  The number of credit points is set at the outset of the project by the responsible teachers, depending on how many fields are tackled in detail and on the expected workload per student.  Regardless of the specific project, each team must consider all steps, within budgetary feasibility, including problem analysis, conceptualization, system and component design, validation, testing, documentation, and presentation.

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.

The course gives an introduction to control in the context of mechatronic systems. As such, it gives a solid foundation of system dynamics and feedback control with a focus on common linear control and analysis methods. Both frequency and time domain methods for system analysis and control design are treated. Moreover, common kinds of industrial servo control systems are introduced and, in particular, treated in exercises, with a focus on electric and hydraulic actuation. Throughout the course, it is discussed how model knowledge is employed for control design and system analysis. Control design, analysis, and simulation are conducted mostly in Matlab / Simulink in this course. The course also contains practical realizations and implementations of controllers, which is mostly done with small mechatronic hardware kits and compatible software. The course's theoretical content includes: Introduction to control and its relation to mechatronics System dynamics, in particular of linear systems in time and frequency domain Feedback control with a focus on linear methods Actuation in mechatronic systems

Palkkien standardiprofiilit, palkin mitoitus, palkin taipuma, kaarevat palkit, hybridipalkit. Pilarin mitoitus ja Euler-nurjahdus. Akselin mitoitus. Väsyminen, ääretön kestoikä ja äärellinen kestoikä, Haigh-Goodman-diagrammi, S-N-käyrä. Ortotrooppinen materiaali. Tasojännitystila ja tasovenymätila. Pääjännitykset 3D-tilassa. Lujuushypoteesit. Paksuseinäiset putket ja painelaitteet.

Palkkien standardiprofiilit, palkin mitoitus, palkin taipuma, kaarevat palkit, hybridipalkit. Pilarin mitoitus ja Euler-nurjahdus. Akselin mitoitus. Väsyminen, ääretön kestoikä ja äärellinen kestoikä, Haigh-Goodman-diagrammi, S-N-käyrä. Ortotrooppinen materiaali. Tasojännitystila ja tasovenymätila. Pääjännitykset 3D-tilassa. Lujuushypoteesit. Paksuseinäiset putket ja painelaitteet.

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.

Introduction to Multiscale material modelling approaches. Phenomenological models to study grain growth and phase transformations in metallic materials during heat treatments. Thermokinetic models to study diffusion kinetics and precipitation in metallic materials during heat treatments. Empirical models to predict manufacturing process parameters and material properties. Finite element models to study the macroscale performance of engineering components based on the microstructural features predicted by the above mentioned modelling approaches. Forming mechanics of advanced composites. Dynamic response of smart laminates. Experimental mechanics and computational modelling of composite materials using Finite element models. Strength and toughness of composite materials. 

Basics of Materials Engineering and Product Design. Principles of materials selection andintroduction to materials selection procedures. Choice of fabrication techniques includingcase studies related to different materials. Selecting polymers and composites as rawmaterials: structure, properties, processing characteristics and applications for thecommercially important polymers including general classes of polymers: commodity,engineering and specialty thermoplastics, thermosetting resins and rubbers. Introduction tospecific metals, alloys and minerals: metallurgy, properties, applications and potentialities ofmetals, alloys and minerals in a wide variety of engineering environments. Wood materials.Introduction to engineering ceramics. Properties and manufacturing of carbon basedmaterials. Recycled Materials as a raw material source. 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.

Tasapaino 3D-tilanteessa, momenttisuureiden vektoriesitys, avaruusristikkorakenteet, sisäiset rasitukset 3D-rakenteissa. Kitka. Virtuaalinen työ. Normaalijännitys ja leikkausjännitys. Aineiden materiaaliominaisuudet. Aksiaalijännitys, taivutusjännitys ja vääntöjännitys. Yksinkertainen leikkausjännitys vs. suora leikkausjännitys. Yhdistettyjen rasitusten aiheuttama jännitystila. Lujuushypoteesit.

Tasapaino 3D-tilanteessa, momenttisuureiden vektoriesitys, avaruusristikkorakenteet, sisäiset rasitukset 3D-rakenteissa. Kitka. Virtuaalinen työ. Normaalijännitys ja leikkausjännitys. Aineiden materiaaliominaisuudet. Aksiaalijännitys, taivutusjännitys ja vääntöjännitys. Yksinkertainen leikkausjännitys vs. suora leikkausjännitys. Yhdistettyjen rasitusten aiheuttama jännitystila. Lujuushypoteesit.