industrial-engineering-Introduction.pptx

Industrial Engineering

1. 1 AE 476 Industrial Engineering Introduction to Industrial Engineering Functional areas of Management Definition and Significance of Industrial Engg . Objectives and Competitive strategies of any manufacturing industry. How Industrial Engg . concepts helps to achieve this? Sub-systems of Operations and its improvement through Industrial Engineering Syllabus. Textbooks and references. Course Faculty: Dr. B. S. GIRISH

2. 2 Functional Areas of Management

3. 3 PRODUCTION/OPERATIONS MANAGEMENT

4. Functional Areas of Management 1- 4

5. Corporate Objectives Objectives - Increasing Profitability: Increasing Profits Growth: Increase market share, Global outreach Return on Investment as early as possible 5

6. Competitive Strategies Today’s manufacturing and service industries face fierce competition Customers demands are rising Challenge for industries to produce goods of right quantity , quality , in time and at minimum cost . Functional Strategies Marketing strategies Financial strategies Personnel strategies Production/Manufacturing strategies 6

7. Production/Manufacturing strategy P/M function aims to provide products/services to its customers by using following strategies: Timely delivery of products/services. Flexibility in meeting customers demand in terms of change in customer demand and change in production volume Quality of products/services to meet customer specifications Cost effectiveness in terms of low price for its products/services relative to that of its competitors. 7

8. Operations subgoals To be effective in manpower cost control Effective material utilization and its cost control Effective facility utilization and its cost control Other objectives achieved: Improves the economy of the nation (GDP) Improves employment opportunities 8

9. What is GDP? Gross domestic product (GDP) is the total monetary or market value of all the finished goods and services produced within a country’s borders in a specific time period. As a broad measure of overall domestic production, it functions as a comprehensive scorecard of a given country’s economic health. 9

10. Operations subgoals Achieving highest efficiency at all operational subsystems

11. 11 Gearing up the operation subsystems to meet delivery commitments

12. 12 Definition of Industrial Engg. American Institute of Industrial Engineers (AIIE) defines Industrial Engineering as follows: Industrial Engineering is concerned with the design, improvement and installation of integrated system of men, materials and equipment . It draws upon specialized knowledge and skills in the mathematical, physical sciences together with the principles and methods of engineering analysis and design to specify, predict and evaluate the results to be obtained from such system.

13. 13 Definition The prime objective of industrial engineering is: 1- To increase the productivity. 2- Eliminating waste and non-value added activities. 3- Improving the effective utilization of resources.

14. 14 Industrial Engineering Approach In carrying out various activities, the industrial engineer: Gathers and analyses facts. Prepares the alternative solutions taking in to consideration all the constraints both internal and external. Selects the best solution for implementation.

15. 15 Objectives of Industrial Engineering The basic objectives of Industrial Engineering departments are: 1- To establish methods for improving the operations and controlling the production costs. 2- To develop programmes for reducing these costs.

16. 16 Techniques of Industrial Engineering Following tools and techniques are used to improve productivity of the organization by optimum utilization of resources. 1- Value Analysis. 2- Production, Planning and Control. 3- Inventory Control. 4- Job Evaluation. 5- Material Handling Analysis. 6-Ergonomics (Human Engineering). 7- Operations Research Techniques. 8- Method Study. 9- Time Study (Work Measurement).

17. 17 1.9 Place of Industrial Engineering in Organization

18. 18 Industrial Engineering in Service Sector Large number of industrial engineers are in demand and attracted to careers in exciting, challenging and rewarding new fields. The various service industries are: 1- Health Service. 2- Government Organizations. 3- Banking.

19. Industrial Engineering (Elective) SYLLABUS Introduction - operations strategy, competitiveness and productivity - product design and process selection – value analysis and value engineering – forecasting - characteristics of production systems - plant location and layout – capacity planning  –  production planning and control – materials requirement planning (MRP) – inventory control – Introduction to work study, time and motion study - Introduction to total quality management (TQM) - Mass Production Management-Line Balancing Techniques. Textbooks: Buffa, E.S. And Sarin, R.K., Modern production /Operations Management, John Wiley & Sons, (1994). I. L. O., Introduction to Work Study: Indian Adaptation, Third (Revised Edition)  Oxford & IBH Publishing Co. Pvt. Ltd. New Delhi, (1997).  References: Muhlemann , A., Oakland, J. O., and Lockyer, K., Productions and Operations Management, Macmillan (1992). Narasimhan , S. L., McLeavey D. W., and Billington , P. J., Production Planning and Inventory Control, Prentice Hall (1977) Barnes, R. M.: Motion and Time Study: Design and Measurement of Work, 7e,John Wiley and sons, New York.(1980) …….. 19

20. Continuous Assessment Quiz-1 (15 marks) Quiz-2 (15 marks) Assignment (20 marks) End Semester Exam (50 marks) Assignments Class Test (MCQ based) – 4 marks Tutorial assignments - 6 marks Case study– 10 marks 20

21. Productivity Crucial to the welfare of the industrial firm as well as for the economic progress of the country. High Productivity: refers to doing work in shortest possible time with least expenditure on inputs without sacrificing quality and with minimum wastage of resources. Definition: Productivity is the quantitative relation between what we produce and what we use as a resource to produce them. It is arithmetic ratio of amount produced (output) to the amount of resources (input). Productivity=output/Input 21

22. Productivity European Productivity Agency (EPA) has defined productivity as “Productivity is an attitude of mind. It is the mentality of progress, of the constant improvements of that which exists. It is the certainty of being able to do better today than yesterday and continuously. It is the constant adaptation of economic and social life to changing conditions. It is the continual effort to apply new techniques and methods. It is the faith in human progress”. 22

23. Productivity Productivity can be increased: Production is increased without increase in inputs. Same production with decrease in inputs. Production is increased with decrease in inputs. 23

24. Productivity Measures Partial Productivity=Total Output/Individual Input Labour Productivity=Total Output/ Labour Input Capital … Material … Energy …. Total productivity=Total tangible output/total tangible input Total tangible output=Value of finished goods produced +value of partial units produced+dividends from securities+other income Total tangible input=value of( human+material+capital+energy+other inputs) 24

25. Expectations from Productivity Management and Entrepreneurs: High return on investment (ROI), High market share and corporate image Managers and Workers: Higher salaries and wages, safer work environment, increased quality of work life. Suppliers: Prompt payment, continuous order. Customers: Lower cost, quality, reliability, safety and timeliness of delivery. Government: Economic development, employment generation, more exports. Share Holders: Higher dividends 25

26. Dynamics of Productivity Change 26 Improvements in Productivity Reduction in Product cost More profits More Savings Increase in demand of goods and services Better machines Higher investments More skilled labour More output

27. DEMAND FORECASTING Plays a crucial role in the development of plans for the future. A fundamental activity of management Forecasting as defined by American Marketing Association “An estimate of sales in physical units (or monetary value) for a specified future period under proposed marketing plan or programme and under the assumed set of economic and other forces outside the organization for which the forecast is made”. 27

28. Demand Forecasting Forecasting is not a guess work. looked upon as a projection based on past data. based on large volume of data on past performance. Long, Medium and short term forecasts Short term: covers period of less than one year. Inventory control, loading and scheduling, budgeting Medium term: one year or five years Aggregate planning- Manpower planning, Subcontracting planning Long term: covers period of five years or more Product diversification Capacity and Investment planning 28

29. Classification of forecasting techniques Judgemental : art of human judgement. Time series methods: based on past data-uses statistical and management science techniques Causal Techniques: tries to establish cause and effect relationship between sales and some other parameters related to sales. e.g. sales-growth of industry, sales-cultural changes, sales-environmental impacts, sales-economic status of the country. Uses coefficient and regression analysis. 29

30. Classification of forecasting techniques Simulation: Imitate customer choices that give rise to demand to arrive at a forecast. Companies simulate customer buying behaviour under dynamic and stochastic environment. Combines time series with causal methods to find answers: What will be the impact of price promotion be? What will be the impact of a competitor opening a store nearby? What will be the impact of price increase? 30

31. Judgemental techniques Market Research: extensive survey and statistical analysis. To get details about location, buyer occupation, prices, quantity, quality, consumer income, etc. Customer and distributor surveys : survey through questionaires given along with guarantee cards. Sales personnel and retails outlets surveys also taken. Marketing trials: applicable to new products. Usually cosmetics and toothpastes. Decision made based on controlled experiments Executive opinion method : non-scientific, biased and subjective. Delphi technique : a panel of experts are asked sequential questionaire in which response to questionaire is used to produce next questionaire . The responses are sent to another experts panel. Through a series of exchanged views a reliable consensus is reached. 31

32. Delphi Technique 32

33. Time Series Analysis Does not study the factors that influence the demand. All factors that shape the demand are grouped in one factor-time Consists of determining the trend underlying the demand and extrapolate the future trend. Methods: Moving average method Weighted moving average method Exponential smoothing method Holts Model and Winters Model Measure of forecast accuracy Mean Absolute Deviation (MAD) Mean Square Error (MSE) Mean Forecast Error (MFE) Mean Absolute Percent Error (MAPE) 33

34. Comparison of forecasting methods 34

35. Measures of forecast error Mean Forecast Error (MFE) MFE= where Best suited in industries where inventory and backlog costs are minimum and at the end of the Nth period the total error is the least Mean Average Deviation (MAD) MAD= where Best suited in industries where inventory and backlog costs are higher and any deviation from error is to be penalised   35

36. Measures of forecast error Mean Square Error (MSE) MSE= where Similar to MAD, but penalizes larger errors Mean Absolute Percentage Error (MAPE) MAPE= where MAPE gives decision maker an idea of how much the forecast is off as a percentage of demand   36

37. Measures of forecast error Bias and Tracking Signal(TS) Bias determines whether a forecasting method consistently over- or under-estimates demand The bias will fluctuate around 0 if the error is truly random and not biased one way or the other. Ideally if we plot all the errors, the slope of the best fit straight line passing through should be zero If the TS at any period is outside the range , this is a signal that the forecast is biased and is either underforecasting (<-6) or overforecasting (+6).   37

38. Methods of forecast Moving Average Method Weighted moving average method Exponential smoothing method 38

39. Methods of forecast Holts Model (trend corrected exponential smoothing) 39

40. Subsequent Classes Characteristics of Production Systems Production Planning and Control ….. 40