Comprehensive Course Structure

The Operations program at Satyendra Chandra Guria Institute Of Management Andtechnology spans eight semesters, with a carefully curated blend of core subjects, departmental electives, science electives, and laboratory work. This structure ensures that students develop both theoretical knowledge and practical skills necessary for success in the field.

Advanced Departmental Electives

The following departmental electives are offered in the Operations program to provide students with in-depth knowledge and specialization opportunities:

• Supply Chain Analytics: This course explores advanced analytics techniques used in supply chain management, including demand forecasting, inventory optimization, and network design. Students learn how to apply statistical models and machine learning algorithms to improve decision-making processes.
• Lean Manufacturing Systems: Focused on lean principles and continuous improvement methodologies, this course teaches students how to eliminate waste, streamline operations, and enhance productivity in manufacturing environments.
• Quality Engineering & Six Sigma: This elective delves into quality control methods and Six Sigma tools for process improvement. Students gain hands-on experience with DMAIC (Define, Measure, Analyze, Improve, Control) frameworks used by leading organizations.
• Operations Research Applications: Building on foundational operations research concepts, this course applies mathematical optimization techniques to real-world problems in logistics, scheduling, and resource allocation.
• Human Factors in Operations: This course examines how human behavior affects operational performance, focusing on ergonomics, team dynamics, and user experience design within complex systems.
• Project Management: Designed to develop skills in planning, executing, and monitoring large-scale projects, this course covers project lifecycle management, risk assessment, and stakeholder communication strategies.
• Business Intelligence & Data Mining: Students explore data analytics tools and techniques for extracting insights from business datasets. This includes predictive modeling, clustering, and classification methods used in decision support systems.
• Manufacturing Systems Design: This course provides an overview of modern manufacturing technologies and design principles, including automation, robotics, and smart factory concepts.
• Operations Consulting: Through case studies and simulations, students learn how to diagnose operational issues, recommend solutions, and implement changes in real-world organizations.
• Sustainable Operations: This course addresses environmental sustainability within operational contexts, exploring green supply chains, carbon footprint reduction, and circular economy principles.

Project-Based Learning Philosophy

The department believes that project-based learning is essential for developing critical thinking, collaboration, and practical problem-solving skills. Projects are designed to mirror real-world challenges faced by industries and organizations.

The structure of projects includes:

1. Mini-Projects (Semester 5-7): These are smaller-scale assignments that allow students to apply concepts learned in class to specific problems. Mini-projects typically last for one semester and involve teams of 3-5 students working under faculty guidance.
2. Final-Year Thesis/Capstone Project: The capstone project is a major undertaking that requires students to conduct independent research or solve a significant problem in their chosen area of specialization. It spans the entire final year and involves extensive literature review, data collection, analysis, and presentation.

Evaluation criteria for projects include:

• Problem identification and scope definition
• Research methodology and data sources
• Analysis and interpretation of results
• Presentation and communication skills
• Teamwork and collaboration
• Innovation and creativity in solution design

Students select projects based on their interests and academic strengths, often aligning with ongoing research initiatives or industry partnerships. Faculty mentors are assigned to guide students through each phase of the project, ensuring they meet learning objectives while fostering independence.