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Mechatronic Systems Engineering and Artificial Intelligence Assignment Help

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Mechatronic Systems Engineering and Artificial Intelligence

Learning Outcomes

Learning Outcome 1: A comprehensive knowledge and understanding of the scientific principles and methodology of System Engineering and AI; including the hardware, software and applications of AI systems.

Ans: A comprehensive understanding of the scientific principles and methodologies underpinning both System Engineering and Artificial Intelligence is crucial. This includes a solid grasp of core system engineering concepts like requirements analysis, system architecture, and lifecycle management, as well as a deep understanding of AI principles such as machine learning, deep learning, natural language processing, and computer vision. Furthermore, this knowledge extends to the practical aspects of AI systems, encompassing the hardware they run on (from specialized processors to cloud infrastructure), the software that powers them (including programming languages, frameworks, and development tools), and the diverse range of applications they enable (spanning areas like robotics, automation, and intelligent decision-making). This combined understanding allows for the effective design, development, and deployment of complex systems that leverage the power of AI.

Learning Outcome 2: Ability to carry out research and apply system engineering and AI concepts for analysis of engineering systems and AI solutions.

Ans: The ability to conduct research and apply system engineering and AI concepts is crucial for analyzing both traditional engineering systems and cutting-edge AI solutions. This involves not only understanding the theoretical underpinnings but also possessing the practical skills to investigate, model, and evaluate these systems. Researchers and practitioners must be able to leverage system engineering principles to design, develop, and integrate AI components effectively, while also using AI techniques to improve and optimize existing engineering systems. This includes applying appropriate methodologies, tools, and techniques for data analysis, system design, and performance evaluation to address complex engineering challenges and advance the field of AI-enhanced systems.

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Learning Outcome 3: Ability to apply system engineering and AI tools for modelling, simulation, design and development of engineering and AI systems.

Ans: The ability to effectively apply system engineering and AI tools is essential for the modeling, simulation, design, and development of both traditional engineering systems and those incorporating artificial intelligence. This involves proficiency in utilizing a range of software and hardware tools relevant to both disciplines. For system engineering, this might include tools for requirements management, system architecture design, and simulation. For AI, it encompasses familiarity with programming languages, machine learning frameworks, and platforms for data analysis and model training. A skilled practitioner can leverage these tools to create accurate models, simulate system behavior, design robust architectures, and develop functional AI components that integrate seamlessly within larger engineering projects, ultimately leading to more efficient and innovative solutions.

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The topics: The topics for the design study this year is: Model Based System Engineering of a smart collaborative robot with vision, voice and IIoT capabilities.

Scope:

The Mechatronic Systemdesign study is an individual assignment in which the student will undertake a design study by adopting the Model Based System Engineering (MBSE) and Model Based Design (MBD)approaches as main methodology for System Integration. At the end of the module, you will have a favour of being the system architect, to integrate multidisciplinary systems, and familiar yourself with the tools and approach used for system integration. The main tools in this case includes the Systems Modelling Language (SysML) (Figure 1) and MATLAB Simulink; other CAD tools may be used to model the system. Modelling and simulation is the key here without the need to have real development. As a design study, no real implementation is required. This helps you develop different skillsets.

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Title: Model Based System Engineering of a smart collaborative robot with vision, voice and IIoT capabilities

Introduction - introduces the subject area and the general focus for the studyto the readers and the background to the work. The section will also define the scope of the work undertaken, indicate the approach taken in the project and introduce the main topics of interest.

Aims and Objectives - this introduces clearly and unambiguously the aims and "SMART" objectives of the study.

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Requirements Specification
- Requirements Specification refers to user requirements, which are then translated into Design Specificationfor the developer by you.

Design Specification- you interpret the user requirements and come up with a design specification

Design concepts and final design(include 2 design concepts) - justify your choice by e.g. a decision matrix against the requirements. Describe your final design showing the system overview which includehardware and software / controller, sensors, actuators.

System Modelling using SysML Models which includes:
Requirement Diagram; Use Case Diagram; Block Definition Diagram/Internal Block Diagram
Parametric Diagram; Activity Diagram/Sequence Diagram; State Machine diagram describing the control logic

Basic Simulink Models and related CAD models, which may include control logic (stateflow). Presentation and description of the results achieved (e.g. modelling (system model) and simulation results, etc.)Other Modelling and Simulation methods or tools are also acceptable. Not expecting a fully operational model.

Results; analysis and discussions; refinement to final designand other major issues which arise in relation to the project undertaken. This section has four purposes, it should: i) Interpret and explain your results; ii) Answer your research question; iii) Justify your approach and iv) Critically evaluate your study.

Conclusions and Recommendations- a review of the study against the objectives identified, a summary of the findings of significance from the work undertaken and the major conclusions that can be inferred. Identify in-particular the novel aspects of the work.

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