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Computational physics — This article is about computational science applied in physics. epub, mobi, pdf, html, pdb, lit, doc, rtf, txt); Computational Liquid Crystal Photonics. Fundamentals, Modelling and Applications, Salah Obayya, Optical.

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Read more icon Embedded Systems. Read more icon Product Lifecycle Management. Read more icon Digital Technical Content Management. Featured Jobs. See more openings. Establishing design requirements and conducting requirement analysis , sometimes termed problem definition or deemed a related activity , is one of the most important elements in the design process, [6] and this task is often performed at the same time as a feasibility analysis. The design requirements control the design of the product or process being developed, throughout the engineering design process.


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These include basic things like the functions, attributes, and specifications - determined after assessing user needs. Some design requirements include hardware and software parameters, maintainability , availability , and testability. In some cases, a feasibility study is carried out after which schedules, resource plans and estimates for the next phase are developed.

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The feasibility study is an evaluation and analysis of the potential of a proposed project to support the process of decision making. It outlines and analyses alternatives or methods of achieving the desired outcome. The feasibility study helps to narrow the scope of the project to identify the best scenario. A feasibility report is generated following which Post Feasibility Review is performed. The purpose of a feasibility assessment is to determine whether the engineer's project can proceed into the design phase.

This is based on two criteria: the project needs to be based on an achievable idea, and it needs to be within cost constraints. It is important to have engineers with experience and good judgment to be involved in this portion of the feasibility study. A concept study conceptualization , conceptual design is often a phase of project planning that includes producing ideas and taking into account the pros and cons of implementing those ideas. This stage of a project is done to minimize the likelihood of error, manage costs, assess risks , and evaluate the potential success of the intended project.

In any event, once an engineering issue or problem is defined, potential solutions must be identified. These solutions can be found by using ideation , the mental process by which ideas are generated.

Engineering Principles for Makers Part One; The Problem. #066

In fact, this step is often termed Ideation or "Concept Generation. Various generated ideas must then undergo a concept evaluation step, which utilizes various tools to compare and contrast the relative strengths and weakness of possible alternatives. The preliminary design, or high-level design includes also called FEED or Basic design , often bridges a gap between design conception and detailed design, particularly in cases where the level of conceptualization achieved during ideation is not sufficient for full evaluation.

So in this task, the overall system configuration is defined, and schematics , diagrams , and layouts of the project may provide early project configuration. This notably varies a lot by field, industry, and product. During detailed design and optimization, the parameters of the part being created will change, but the preliminary design focuses on creating the general framework to build the project on. Blanchard and J. There will be a series of lectures and presentations with students selected to follow up on one of these i. This module will introduce the fundamental concepts of lean manufacturing and six sigma.

This includes continuous improvement and statistical methods for problem solving. It will cover the understanding of lean manufacturing in the area of voice of customer, waste elimination, value stream management and the methods for improving process flow. This module introduces the students to systems modelling and engineering problem solving by modelling.

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The overall aim is to help the student achieve an understanding of systems modelling and how problems in engineering can be solved by modelling. Systems analysis and modelling takes into account the variability and uncertainty that exists in many engineering problems Systems analysis and modelling covers Design of Experiments and optimization. The lectures will be complemented by computer classes to provide an introduction to major software packages used in the industry such as Solidworks and ANSYS for modelling and analysis to prepare students for future academic study and increasing reliant of industry on highly sophisticated and multi-functional software.

They will learn that such microprocessors are embedded and are programmed to use sensors and actuators to control the operations mechanics in this case of the systems for example, a mobile robot or a driverless car. It will be explained that a mechatronic system is the integration of various engineering disciplines and from another perspective, the integration of the mechanical system with sensors and actuators to the information processing and control system. Sensors and actuators are already covered in Electromechanical Systems, and mechanical components, in other modules.

The design of mechatronic systems will be presented. Various design concepts and tools will be introduced, including functional diagrams. Students will apply them in case studies, and research into emerging technologies in smart product systems. They will be introduced to portable energy source and their characteristics. The basics of microprocessor architecture and operations will be taught and the key differences in their applications in embedded systems unlike that for general computing will be highlighted.

These include pertinent programming tools and programming for real time.

To realise a system, prototyping are often used. A brief mention of mechanical components prototyping e. System prototyping for model based design using system modelling, hardware in the loop HIL and software in the loop SIL will be introduced. Motion control system is as much a mechatronic system as well as a control algorithm in the embedded system.

Their goals are the same. In this module, the various types of algorithms and implementation in the processor will be discussed. There are two main parts in this module: robot manipulators and mobile robots. In each of these modules, the concepts of kinematics, constraints, and control will be taught. In mobile robotics, students will learnt about wheels locomotion, in particular, the differential drive wheel robots similar to many commercial robotic vacuum cleaners.

They will be introduced to various types of wheel geometries and the constraints they impose on a robotic body. Mathematical models will be derived, and students will learn how use the models to manipulate and control the robot in motion.

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In addition, students will be taught types of relevant sensors, navigation techniques, types of control architecture and robot behaviour that are found in autonomous mobile robots. In robot manipulator, students will learn how links and joints are configured for different tasks in the industry. They will be taught, in forward kinematics, how to determine the robot end effector pose position and orientation using Denavit-Hartenberg homogenous transformations, and in inverse kinematics, to determine the joint variables given the end effector pose.

They will apply what they have learnt in Dynamics to derive the Newton-Euler dynamic equations of the manipulator, and subsequently learn the Euler-Lagrange approach using work-energy principle to arrive at the same equations. In addition, students will learn about independent joint control using PID compensators, and basic concepts of multivariable control, hybrid control, impedance control and non-linear control.

The current and future trend of mobile and manipulator robots in social and service robotics will be discussed. This will be done through videos and seminar discussions. Industrial Automation encompasses the whole chain from sensors, motors, controllers, communication networks, operator visualization, archiving and up to manufacturing execution systems and enterprise resource management. It includes fault-tolerance against hardware and software faults and the evaluation methods.

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This module will introduce students the major components of a modern automation system and explain their key principles. Basic software design techniques, including sequential logic control, ladder diagram programming, and industrial automation controllers such as PLC and Distributed Control Systems. Introduction to commercially available offline-based robot programming softwares will also be introduced as a hands-on activity.

Economic and risk assessment of implementing automation. This is a specialised module that focusses on a holistic view of the whole manufacturing ecosystem. Students will learn about management systems from the production shop floor to the enterprise level, together with engineering principles and operational tools to improve manufacturing processes.

At the start of the module, students will be given an overview of different types of products and production shop floor processes including factory layout and machinery organisation before learning about mid-tier management systems, i. This then leads to exposure to the top-tier corporate management system which is governed primarily by Enterprise Resource Planning ERP. Students will also have the opportunity to learn first-hand the logistics and communication processes of shop floor operations with managements systems through actual production layouts set up in laboratory sessions.