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M. Stat. – 512
Statistical Methods in Industrial Management
Full marks – 75
(Examination 60, Tutorial/Terminal 11.25, and Attendance 3.75)
Number of Lectures – Minimum 45
(Duration of Examination: 4 Hours)

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Aim of the Course:
In Industrial management prepares students to take on management responsibility is the middle management in private industry, the service sector or public administration.
Objective of the Course: 
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To deepen and broaden the student’s knowledge.
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To cover the theory and practice of modern econometric.
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To teach the students the habits of thought knowledge are understanding.
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The course is application oriented.
Learning Outcomes:
Student will be able to:
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Perform the management functions.
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Compare selected theories of management.
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Perform the functions is the marketing mix.
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Use basic nosiness application.
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Assessor ethical issue in business situation

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Course Contents
Industrial management: Meaning, Principles, Characteristics and importance. Management by objectives. Advantages and disadvantages of management by objectives. Industrial organization chart. Decision making techniques. Industrial accidents and safety. Causes of accidents. Methods of reducing accidents. Job analysis and evaluation. Methods of job analysis and evaluation. Production and productivity. Factors of production. Tools of productivity. Factors affecting productivity.
Industrial Psychology: Quality, Scope and Aims of industrial psychology, Problem of industrial psychology, Pattern of human behavior, Human needs, Difficulties and suggestion for improvement of human and  social relationships.
Quality control and inspection: Objectives of quality control. Quality conformance. Quality principles. Advantages of quality control. Quality certification, Objectives of inspection. Various kinds of inspection. Advantages and disadvantages of inspection. Quality philosophies. Deming philosophy. Tools and techniques. Total quality management (TQM). Implementation of TQM, Philosophies of TQM. Pareto analysis, Cause-and-effect-diagrams. Failure modes and effect analysis (FMEA).
Corrective maintenance (CM) and preventive maintenance (PM): Preventive maintenance models for complex systems. Maintenance of repairable systems. Models for complex repairable systems. Parameter estimation. Model selection. Preventive maintenance scheduling. Reliability centered maintenance (RCM). Steps of the RCM process. Inventory. Managing and controlling inventory. Forecasting for inventory management of service parts. Supply-chain management.  Case studies in industrial management and maintenance.
Network Analysis: Network Techniques. Project Management, Key decisions in project management, Project life cycles, planning and scheduling with Gantt Charts, PERT and CPM strategies, Steps in PERT and CPM project Plan. Deterministic time estimate, Probabilistic time estimate.

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Main Books:
1)
Mukhi, H. R. (2001): Industrial Management, Satya Prakashan, New Delhi.
2)
William J. Stevenson (2005): Operation Management, 8th edition, McGraw Hill Company, N.Y.
Books Recommended:
3)
Davis Aquilano and Chase (2004): Fundamentals of operation Management, 4th ed.,  McGraw Hill Company, N.Y.
4)
Hill, T. (2000): Operations Management: Strategic, Context and Managerial Analysis, University of Oxford.
5)
Hiller and Hiller (2005): Introduction to Management Science, 2nd ed., McGraw Hill Company, N.Y.
6)
Kelly A. and Harris, M.J. (1978): Management of Industrial Maintenance,  Butterworth Heinemann Ltd.
7)
Kobbacy, K.A.H and Murthy, D.N.P. (2008): Complex System Maintenance Handbook, Springer-Verlag.
8)
Zipkin (2005): Fundamental of inventory Management, 1st ed., McGraw Hill Company, N.Y.