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The MS and PhD Design and Manufacturing Engineering programme is targeted to produce skilled engineers with multi-disciplinary knowledge in product design and development, manufacturing processes and management, industrial engineering and related corporate affairs. It aims to provide such an education and research environment that will help reduce the gap between industry and academia. Furthermore, with the availability of the four different fields of study, i.e. Design, Manufacturing, Smart Manufacturing and Engineering Management, the graduates can have a better chance of employment to fulfil the market needs by selecting their choice of field of work. Recent technological advancements in manufacturing and management necessitate the knowledge of smart manufacturing, intelligent manufacturing, digital manufacturing, Internet of Things (IoT) and Industry 4.0. Furthermore, IoT has integrated into industrial management especially supply chain management, project management, quality and reliability management and operations management. Thus, integrating these fields into smart manufacturing. Generally, Industry 4.0 describes the growing trend towards automation and data exchange in technology and processes within the manufacturing industry, including: a. The internet of things (IoT) b. The industrial internet of things (IIoT) c. Cyber-physical systems (CPS) d. Smart manufacturing e. Smart factories f. Cloud computing g. Cognitive computing h. Artificial intelligence This automation creates a manufacturing system whereby machines in factories are augmented with wireless connectivity and sensors to monitor and visualize an entire production process and make autonomous decisions. Educational Program Objectives Following objectives are to be achieved: - a. To understand the concepts of IoT for implementation in different design and manufacturing products. b. To increase the capability of the students by learning advanced programming skills using newly developed software, for example, Python for engineers. c. To gain knowledge of corporate governance and leadership in the industry. d. To equip the students with the newly developed technologies like machine learning for human machine interaction and artificial intelligence application in the manufacturing industries. e. Competency in advanced manufacturing processes is required for the development of 21st century products. f. Capability to enhance the performance of the industrial organization by effectively managing human resources. g. To enhance the knowledge of automation by implementing the excessive application of artificial intelligence. h. To develop automation skills that could effectively manage the interdisciplinary problems arising the manufacturing organizations
Programme overview
Main Subject
Engineering - Manufacturing and Production
Degree
PhD
Study Level
PHD
Study Mode
On Campus
The MS and PhD Design and Manufacturing Engineering programme is targeted to produce skilled engineers with multi-disciplinary knowledge in product design and development, manufacturing processes and management, industrial engineering and related corporate affairs. It aims to provide such an education and research environment that will help reduce the gap between industry and academia. Furthermore, with the availability of the four different fields of study, i.e. Design, Manufacturing, Smart Manufacturing and Engineering Management, the graduates can have a better chance of employment to fulfil the market needs by selecting their choice of field of work. Recent technological advancements in manufacturing and management necessitate the knowledge of smart manufacturing, intelligent manufacturing, digital manufacturing, Internet of Things (IoT) and Industry 4.0. Furthermore, IoT has integrated into industrial management especially supply chain management, project management, quality and reliability management and operations management. Thus, integrating these fields into smart manufacturing. Generally, Industry 4.0 describes the growing trend towards automation and data exchange in technology and processes within the manufacturing industry, including: a. The internet of things (IoT) b. The industrial internet of things (IIoT) c. Cyber-physical systems (CPS) d. Smart manufacturing e. Smart factories f. Cloud computing g. Cognitive computing h. Artificial intelligence This automation creates a manufacturing system whereby machines in factories are augmented with wireless connectivity and sensors to monitor and visualize an entire production process and make autonomous decisions. Educational Program Objectives Following objectives are to be achieved: - a. To understand the concepts of IoT for implementation in different design and manufacturing products. b. To increase the capability of the students by learning advanced programming skills using newly developed software, for example, Python for engineers. c. To gain knowledge of corporate governance and leadership in the industry. d. To equip the students with the newly developed technologies like machine learning for human machine interaction and artificial intelligence application in the manufacturing industries. e. Competency in advanced manufacturing processes is required for the development of 21st century products. f. Capability to enhance the performance of the industrial organization by effectively managing human resources. g. To enhance the knowledge of automation by implementing the excessive application of artificial intelligence. h. To develop automation skills that could effectively manage the interdisciplinary problems arising the manufacturing organizations
Admission Requirements
Sixteen years of schooling or 4 years education after HSSC/A’ Level in relevant discipline with minimum CGPA of 2.0 out of 4.0 OR 55% marks (percentage will only be considered if CGPA is not mentioned on the transcript). GAT (General) conducted on or after 1st May 2022 till 31st May 2024 by NTS with at least 50 accumulative test score or Higher Education Aptitude Test (HAT) conducted by HEC on or after 1st May 2022 till 31st May 2024 with at least 50 accumulative test score or NUST Aptitude Test (NAT) with at least 50 accumulative test score or GRE (General) conducted by ETS, USA, with following minimum score separately in each section: - Description Scale Quantitative 151/170 Verbal 146/170 Analytical Writing 3.5/6.0
Domestic
101,780
Domestic (Out of State)
101,780
International
3,050
Scholarships
Selecting the right scholarship can be a daunting process. With countless options available, students often find themselves overwhelmed and confused. The decision can be especially stressful for those facing financial constraints or pursuing specific academic or career goals.
To help students navigate this challenging process, we recommend the following articles:
PhD Design and Manufacturing Engineering
NUST Main Campus, Islamabad, Pakistan
3,050 Tuition Fee/year
Engineering - Manufacturing and ProductionMain Subject Area
Programme overview
Main Subject
Engineering - Manufacturing and Production
Degree
PhD
Study Level
PHD
Study Mode
On Campus
Programme overview
Main Subject
Engineering - Manufacturing and Production
Degree
PhD
Study Level
PHD
Study Mode
On Campus
Admission Requirements
Domestic
Domestic (Out of State)
International
Scholarships
Selecting the right scholarship can be a daunting process. With countless options available, students often find themselves overwhelmed and confused. The decision can be especially stressful for those facing financial constraints or pursuing specific academic or career goals.
To help students navigate this challenging process, we recommend the following articles:
How to get a full scholarship
Looking for a fully-funded scholarship to see you into university? Find out how to boost your chances of getting one.
Scholarships to study abroad
Find scholarships to study abroad with our lists of international scholarships – categorized by country, by subject, and by type of student.
Scholarship Applications: Frequently Asked Questions
Get answers to all your questions about scholarship applications, including tips on how to find scholarships and chances of success.
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