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Presentation
Presentation
The programme presents concepts that highlight Operations Management in a global and competitive market. The manufacturing sector faces new challenges with complex supply chains and fragmented production. Economies are revitalising this sector with smart production strategies in line with SDG 9 - Industry, Innovation and Infrastructure and SDG 12 - Sustainable Consumption and Production. Automation and data analysis increase efficiency and reduce waste, and it is crucial to discuss the application of these principles and analyse scientific articles to support sustainable solutions.
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Class from course
Class from course
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Degree | Semesters | ECTS
Degree | Semesters | ECTS
Master Degree | Semestral | 6
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Year | Nature | Language
Year | Nature | Language
1 | Mandatory | Português
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Code
Code
ULP6573-8209
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Prerequisites and corequisites
Prerequisites and corequisites
Not applicable
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Professional Internship
Professional Internship
Não
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Syllabus
Syllabus
Introduction to operations management; Operations strategies; Product development and process selection; Forecasting; Aggregate planning; Capacity management; Scheduling of operations; Facility configuration; Stock management; IT in Production.
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Objectives
Objectives
Identify the role of operations management in organisations: Related to SDG 9 - Industry, Innovation and Infrastructure, emphasising efficiency and sustainable innovation in operations. Discuss the strategic impact of new product development: Aligned with SDG 12 - Sustainable Production and Consumption, promoting sustainable design. Apply forecasting methods and calculate forecasts: Linked to SDG 8 - Decent Work and Economic Growth, by improving efficiency. Capacity planning and location of facilities: Linked to SDG 11 - Sustainable Cities and Communities, by considering local impacts. Discussing the impact of IT on production: In line with SDG 9, by promoting sustainable technological innovation.
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Teaching methodologies and assessment
Teaching methodologies and assessment
An active, student-centred, learning-by-doing methodology will be adopted. As well as favouring the appropriation of theoretical and conceptual knowledge, it aims to train students in the main means of intervention, through concrete opportunities for action. These experiences will be discussed and reflected on by the students in order to promote their integration. Methodologies include: Theoretical-practical integration Research with tutorial guidance Fieldwork Case studies with problem solving (Problem Based Learning) Assessment: Preparation of a reading sheet, which will be presented and analysed in class - 35%. Final work: Written work - 30%; Research with supervision - 10%; Presentation - 25%
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References
References
Cachon, G. & Terwiesch, C. (2019). Matching Supply with Demand: An Introduction to Operations Management (4thEd), McGraw-Hill Education. Choi, T. M., Kumar, S., Yue, X., & Chan, H. L. (2022). Disruptive technologies and operations management in the Industry 4.0 era and beyond. Production and Operations Management, 31(1), 9-31. Petri Helo & Yuqiuge Hao (2022) Artificial intelligence in operations management and supply chain management: an exploratory case study, Production Planning & Control, 33:16, 1573-1590, DOI: 10.1080/09537287.2021.1882690 Reid, R. Dan e Sanders, N. A. (2015), Operations Management (6th Edition), John Wiley & Sons, Inc. ISBN: 978-1118952610. Slack, N., Brandon-Jones, A., & Burgess, N. (2022). Operations Management (10th Edition). Zhou, L., Jiang, Z., Geng, N., Niu, Y., Cui, F., Liu, K., & Qi, N. (2022). Production and operations management for intelligent manufacturing: A systematic literature review. International Journal of Production Research, 60(2), 808-846.
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Office Hours
Office Hours
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Mobility
Mobility
No