The objective of the course is to introduce the basic concepts and statistical and other quantitative techniques and methods employed in the broad area of materials management, in general and inventory control and management, in particular. Static and dynamic inventory problems under certainty, risk and uncertainty, design of inventory study and decision procedures, current approaches in inventory management, important methods and approaches in purchasing, storing, distribution, value engineering/analysis, logistics and SCM are some of the topics which are required to be covered for the students taking up this course for the first time. Such a comprehensive course is required to be offered by Mechanical Engineering, Industrial Engineering,Manufacturing/Production Engineering and related departments at undergraduate level and by Management/Business schools at the postgraduate level in any renowned university or educational institute in India and abroad. It is essential that the students studying in these disciplinesat UG or PG levels should enroll themselves in this course.INTENDED AUDIENCE: Management, Industrial Engineering, Mechanical Engineering, Production Engineering and related disciplines.PREREQUISITES : NilINDUSTRY SUPPORT : Tata Steel, Tata Motors, L&T, Linde and similar such manufacturing and service organizationsincluding IT companies
Overview
Syllabus
Week 1 : Introduction to Inventory and Materials Management: Concepts and Issues,Types of inventory,Inventory costs and their measurement, Structure of inventory models, Importance and areas of materials management.
Week 2 : Inventory Problems and Selective Inventory Management: Classification of inventory problems, Importance-based classification of inventory, selective inventory management techniques and their use, Numerical problems.
Week 3 : Static Inventory Problems under Risk: General characteristics, Opportunity cost matrix and cost structure, Mathematical formulations (discrete and continuous cases), Imputation of costs, Numerical problems.
Week 4 : Static Inventory Problems under Uncertainty: General characteristics, Decision criteria for uncertainty and inventory problems, Distribution-free analysis (Tchebycheff and other inequalities), Comparison of analyses with full and partial information, Numerical problems.
Week 5 : Dynamic Inventory Problems under Certainty: General characteristics, Fixed Order Size System (EOQ and its variants), Economic Production Quantity (EPQ), Fixed order interval system, Inventory problem formulation and solution under constraints, Numerical problems.
Week 6 : Dynamic Inventory Problems under Risk: General characteristics, Types of inventory control systems with known stock-out costs and service levels, Approximate and exact methods for safety stock determination, Numerical problems.
Week 7 : MRP, MRP-II and DRP: Concepts and Issues of MRP, Design of MRP system and its variants (MRP-II and DRP), Numerical problems.
Week 8 : JIT-based Approaches for Materials Management: Concepts and Issues, Relationship with Lean Engineering practices, Design of JIT-based inventory management systems, Numerical problems.
Week 9 : Basics of Purchasing Management: Fundamentals and importance of industrial purchasing, Types of purchasing, Related techniques (non-quantitative and quantitative) in purchasing, Measurement and evaluation of performance of suppliers and purchasing systems,Numerical problems.
Week 10 : Theory of Constraints and Materials Management: Concept and Issues, Bottleneck and non-bottleneck resources, Process and transfer batches, Capacity constraint resources, D-B-R scheduling and VAT plants, Effect on materials management, Numerical problems.
Week 11 : Value Engineering/Analysis and Stores Management: Objectives and issues of Value Engineering/Analysis(VE/VA), Steps in VE/VA, Effects on purchasing and materials management, Basics of and approaches for stores management, Numerical problems.
Week 12 : Logistics and Supply Chain Management: Trends and issues, Push versus Pull distribution system, Basic Issues in Design for Logistics, SCM, and Greening SC, Inventory system development, Numerical problems.
Week 2 : Inventory Problems and Selective Inventory Management: Classification of inventory problems, Importance-based classification of inventory, selective inventory management techniques and their use, Numerical problems.
Week 3 : Static Inventory Problems under Risk: General characteristics, Opportunity cost matrix and cost structure, Mathematical formulations (discrete and continuous cases), Imputation of costs, Numerical problems.
Week 4 : Static Inventory Problems under Uncertainty: General characteristics, Decision criteria for uncertainty and inventory problems, Distribution-free analysis (Tchebycheff and other inequalities), Comparison of analyses with full and partial information, Numerical problems.
Week 5 : Dynamic Inventory Problems under Certainty: General characteristics, Fixed Order Size System (EOQ and its variants), Economic Production Quantity (EPQ), Fixed order interval system, Inventory problem formulation and solution under constraints, Numerical problems.
Week 6 : Dynamic Inventory Problems under Risk: General characteristics, Types of inventory control systems with known stock-out costs and service levels, Approximate and exact methods for safety stock determination, Numerical problems.
Week 7 : MRP, MRP-II and DRP: Concepts and Issues of MRP, Design of MRP system and its variants (MRP-II and DRP), Numerical problems.
Week 8 : JIT-based Approaches for Materials Management: Concepts and Issues, Relationship with Lean Engineering practices, Design of JIT-based inventory management systems, Numerical problems.
Week 9 : Basics of Purchasing Management: Fundamentals and importance of industrial purchasing, Types of purchasing, Related techniques (non-quantitative and quantitative) in purchasing, Measurement and evaluation of performance of suppliers and purchasing systems,Numerical problems.
Week 10 : Theory of Constraints and Materials Management: Concept and Issues, Bottleneck and non-bottleneck resources, Process and transfer batches, Capacity constraint resources, D-B-R scheduling and VAT plants, Effect on materials management, Numerical problems.
Week 11 : Value Engineering/Analysis and Stores Management: Objectives and issues of Value Engineering/Analysis(VE/VA), Steps in VE/VA, Effects on purchasing and materials management, Basics of and approaches for stores management, Numerical problems.
Week 12 : Logistics and Supply Chain Management: Trends and issues, Push versus Pull distribution system, Basic Issues in Design for Logistics, SCM, and Greening SC, Inventory system development, Numerical problems.
Taught by
Prof. Pradip Kumar Ray
