How to Capture Quality Data for Cost Engineering

1. How to Capture Quality Data for Cost Engineering Professor Rajkumar Roy r.roy@cranfield.ac.uk Cranfield University ACostE Learning Event, 2nd November 2005

2. I want 5% Cost Reduction this year! ACostE Learning Event, 2nd November 2005

3. Time is changing ... ACostE Learning Event, 2nd November 2005

4. Decision Engineering Fact based Negotiation ! ACostE Learning Event, 2nd November 2005

5. Cost Data : Challenges ! We have plenty of data! Lacks right structure! Not enough! ACostE Learning Event, 2nd November 2005

6. Cost Data and Information: Challenges ! Many OEM’s are losing product realisation knowledge ! ACostE Learning Event, 2nd November 2005

7. Opportunities ! Collaboration! Structured Cost Data Collection! Benchmark Database! Enterprise Resource Planning (ERP) software ACostE Learning Event, 2nd November 2005

8. Project Phases A B C D E F Percentage expected error 100 Worst range of expected accuracy 80 Best range of expected accuracy 60 40 20 0 -20 -40 Rough Order of Magnitude Feasibility studies Preliminary estimate Definitive estimate Detailed Estimates -60 Class 1 Class 2 Class 3 Class 4 Class 5 Calendar Time (No Scale) Types of cost estimates vs Product Realisation Product Realisation ACostE Learning Event, 2nd November 2005

9. Major Cost Engineering Techniques • Parametric cost estimating • Detailed cost estimating • Analogy based cost estimating ACostE Learning Event, 2nd November 2005

10. Each Cost Engineering Technique requires different type of data and information... ACostE Learning Event, 2nd November 2005

11. Sources of Cost Engineering Data • Engineering Drawings • Bills of Materials • Process/Routing Sheets • Master Production Schedules • Accounting Records • Supplier and Catalogue information • Labour Rates and Standard time Data • Repair and Maintenance Schedules • ERP Systems ACostE Learning Event, 2nd November 2005

12. Team Members • Need experience • Should be carefully selected to ensure reliable cost data is obtained • Design and technical experts can provide: • Design and Development costs/estimates • Manufacturing and Assembly experts can provide: • Equipment, tooling, material, production, and in-process handling costs/estimates ACostE Learning Event, 2nd November 2005

13. Team Members cont. • Industrial Engineers can provide: • Quality control, reliability, and production volume based on standard times • Shipping and Warehouse experts can provide: • Material handling, storage policies, packaging, receiving and shipping costs • Accountants can provide • Overhead, administrative, and related cost figures • Marketing can provide • Distribution and Marketing costs ACostE Learning Event, 2nd November 2005

14. Types of Cost Data • Quantitative • Qualitative ACostE Learning Event, 2nd November 2005

15. Defined as the Drivers Whose Primary Data can be Collected in the Form of a Number. • E.g. Mass, Length, Velocity, Weight. Quantitative Cost Drivers ACostE Learning Event, 2nd November 2005

16. Qualitative Cost Drivers Defined as Drivers Whose Primary Data is Subjective and Open to Opinion. It Needs Conversion into a Numeric Form. • E.g. Manufacturability, Complexity, Quality, Aesthetics. ACostE Learning Event, 2nd November 2005

17. DIY! Attendees will be divided into groups. Each group will identify the following: What do you mean by ‘Quality’ Data? What are the possible sources of inaccuracies in data? Present your views! Time: 30 mins ACostE Learning Event, 2nd November 2005

18. Capturing Quality Cost Data • Questionnaire • Interviews • Case Study • Desk Research • Business Intelligence ACostE Learning Event, 2nd November 2005

19. Data Collection, Organisation and Normalisation • Cost Data and non cost data • Sources of data • Cost Data: Management Information System • Non Cost Data: MIS (ERP), engineering drawings, specifications, interviews • Normalisation of data • production rate • improvement curve • inflation ACostE Learning Event, 2nd November 2005

20. Data Collection, Organisation and Normalisation - the process • Very Important Stage • Can Be Time-Consuming • Need Actual Historical Cost, Schedule, and Technical Information • Identify Standard Sources • Search Out New Sources if necessary • Capture Historical Data • Challenge Data Quality • Provide Sufficient Resources ACostE Learning Event, 2nd November 2005

21. Data Normalisation - process flow Source: NASA handbook ACostE Learning Event, 2nd November 2005

22. Data Evaluation ! • Sufficient data ? • Physical significance of data? • Data collection methodology ? • Are cost, technical, and program data collected in a consistent format? • Procedures to identify and examine any data anomalies? • Any adjustment required? • Documentation of adjustments? ACostE Learning Event, 2nd November 2005

23. Collecting Cost Data for Parametric Cost Estimating ACostE Learning Event, 2nd November 2005

24. LONGERON RADAR FRAME SPIGOT FRAMES CASE STUDYMetallic Parts ACostE Learning Event, 2nd November 2005

25. Independent Variable 3D Model 3D Model Independent Variable Geometry Lines Arcs Curves Points Shapes Primitives Nodes DECOMPOSE CSG Tree Independent Variable File Size Data table Index Conceptual Stage ‘A’ Schemes 3D Model 40% OF COSTS Quantitative Cost Drivers Est. Direct Cost ACostE Learning Event, 2nd November 2005

26. Old Customer • Existing Aircraft • Futuristic Aircraft • New Customer Qualitative Cost Drivers Categories for Rating CATIA Competency Design Experience • Ease of Customer Req. Capture Estimated Indirect Cost • Designer’s experience / skill level • Intricacy of parts design • Project Size • Experience of • design domain • Likelihood of Eng. Changes • Simplicity of Requirements New Materials New Technology New Processes • % of new design / modification • Ease of interface Totally New Design Simple Modifications 60% OF COSTS Expertise ACostE Learning Event, 2nd November 2005

27. Sample Data - Frames ACostE Learning Event, 2nd November 2005

28. Feature Approach Cost Estimating Relationships (CER) Total Time = QN Time + QL Time + Allocations Total Time = C11 + C12(Mass) + C13(Surface Related) + Allocations CATIA Approach Total Time = C14 + C15(Mass) + C16(Surface Related) + Allocations C11 … C16 are constants ACostE Learning Event, 2nd November 2005

29. For a less experienced designer : High Complex Part + 50 % Low Complex Part + 30 % QUALTITATIVE DATA: Problem! ACostE Learning Event, 2nd November 2005

30. Learning Outcomes! • Understand the design process • Do not mix too dissimilar products • Collect as much data as possible • Verify the quantitative data for physical significance • Cross check the qualitative data, take more opinions • Educate designers about quantitative and qualitative cost drivers • Do not depend entirely on statistical analysis to develop the relationships, use common sense and experience too • Identify Risk • Do not use too many variables within the CERs • Do not mix the quantitative and qualitative cost drivers • Always validate the CERs for physical significance ACostE Learning Event, 2nd November 2005

31. Capturing Cost Data for Detailed Cost Estimating ACostE Learning Event, 2nd November 2005

32. Obtaining Required Cost Data • Where can the required cost data be obtained from? • Internet search engines – Google, MSN, Lycos, Yahoo • Industrial & business journals, manufacturing magazines • Contacting known trade unions & associations • Trade exhibition visits • Known and existing suppliers catalogues ACostE Learning Event, 2nd November 2005

33. Data Collection Methodologies • Efficient Data Collection Process • Design data collection templates • Templates, Suppliers contact details • Create database in order to request, collect and store data • Central storing point, repository of data source • Ensure consistency in collecting and storing data • Definition of data collection process relative to the data store, this ensures efficiency • Ensure consistency in requesting the required data • Email templates reduce time taken to request information from suppliers, requisition process defined ACostE Learning Event, 2nd November 2005

34. Possible Sources of Cost Data • Labour Rates: • Office of National Statistics - (ASHE Data) • Incomes Data Statistics - Average Earnings Index • CELRE Survey House - Salary Survey Engineers • Hays Personnel - Engineering - Salary Survey • Payscale - Salary Survey • CNEL (Italy) - Portale CNEL • Online Recruitment Agencies • www.monster.co.uk • www.monster.fr ACostE Learning Event, 2nd November 2005

35. Possible Sources of Cost Data • Labour Rates – www.monster.co.uk ACostE Learning Event, 2nd November 2005

36. Possible Sources of Cost Data • Equipment – www.dmguk.com ACostE Learning Event, 2nd November 2005

37. Possible Sources of Cost Data • Materials – Corus Steels U.K, www.corusgroup.com ACostE Learning Event, 2nd November 2005

38. Challenges Faced in Data Collection • Possible Challenges Encountered; • Trade unions & associations may not hold required information • Email addresses and telephone no’s obsolete • Companies refusing to provide data • Considered sensitive • Unavailable online • Fee required by data source for processing of data ACostE Learning Event, 2nd November 2005

39. Normalization of Materials Cost Data • Materials: Magnesium Sheet • ‘Raw’ costs imported into Excel for Normalization Magnesium Sheet ‘Raw’ Cost Data ACostE Learning Event, 2nd November 2005

40. Normalization of Labour Cost Data • Labour Rates: U.K by industrial sector ACostE Learning Event, 2nd November 2005

41. Normalization of Equip. Cost Data • Equipment: CNC Lathes • Equipment grouped based on dimensions and power output (main spindle) • Equipment grouped and average value (cost) taken from equipment based on dimension or power group ACostE Learning Event, 2nd November 2005

42. V-CES Service ACostE Learning Event, 2nd November 2005

43. V-CES Service • Provide Cost Engineering Training for: • Aerospace • Automotive • Semiconductor OEM’s • Online and offline services targeted to the needs of cost engineering professionals, design and manufacturing engineers. • Virtual infrastructure for European OEMs and their suppliers to share cost engineering practices. • V-CES is funded by the European Commission to enhance competitiveness of European industry, in particular for SMEs. ACostE Learning Event, 2nd November 2005

44. V-CES Cost Database • The V-CES cost database has been developed to support the V-CES cost estimating mentor • Definition of V-CES cost database; • Provide the cost estimator using the V-CES service the required value of their chosen factors • Factors include: • Average Equipment Values • Average Material Values • Annual Labour Rates ACostE Learning Event, 2nd November 2005

45. Equipment Data Structure ACostE Learning Event, 2nd November 2005

46. Populating V-CES_Cost_db • MySql, PHP Admin: CNC_Lathe_Dimensions_db ACostE Learning Event, 2nd November 2005

47. Brainstorming! Please work together with your neighbor: Identify the challenges in data collection for your cost estimating tasks. Let’s discuss your views! Time: 15 mins ACostE Learning Event, 2nd November 2005

48. Concluding Remarks Cost Estimating with good quality Data is becoming very important Benchmark Databases are required A structured approach to Data Collection and Analysis is the key to success ERP systems could provide good quality Data and Information for Cost Engineering. ACostE Learning Event, 2nd November 2005

49. Thank You! www.cranfield.ac.uk/sims/cost ACostE Learning Event, 2nd November 2005