IS 3315: Manufacturing Systems

1. IS 3315: Manufacturing Systems Part 1: The organisation of Manufacturing firms • Understand the basic business processes • understand the basic flows of information • know the basic systems / sub systems implemented • understand their linkages

2. Basic business processes Designing Building Selling Buying Processing orders Getting paid Paying 1 – Arrange these in sequence 2 – name proper departments

3. Basic flows of information • Organisations are organised in a number of functional areas • They collect and organise data to support their complementary missions • they interact and collaborate in managing the organisation

4. Examples • Finance: managing the cash flows, providing resources to the firm • Marketing: promoting the firm and its products • Sales: selling the products; dealing with customers • Production: manufacture goods • These are broken down further into sub areas Name some of these sub areas

5. Collaboration / Conflict between areas • All areas of the firm must exchange info with the others (just like organisations must interact with the outside) • divergence of viewpoints means there are opportunities for conflict • managing same resources / using the same assets but with radically different goals Describe situations involving these conflicts

6. Examples: • Quality control versus production • Procurement versus production • Dealing with customer returns • Sales and accounting Explain the underlying cause of these conflicts

7. Manufacturing Organisations • Business Processes more complex • Lead time must be built into process of planning for demand • Scheduling of resource use is more complex • productivity is a composite indicator which measures many operators’ work together • the definition of productivity / the way it is measured affects the results

8. al 1 W3 Shipping al 2 al 1 WP2 storage W2 Stocks Finished Goods al 2 Main Corridor al 1 WP1 cooling W1 al 2 Changing Rooms and Related Facilities Stocks RM Preparation ovens Quality Control Illustration

9. Collaboration and Information • Functional areas cannot collaborate if no information circulates • first stage: people talk to one another • then exchange of documents • then develop integrated systems shared by several functional areas / the whole firm • This requires the existence of common definitions and reliable / undisputed sources of data • Also people must have incentives to collaborate

10. Reliable Common Grammar: Examples • Sales statistics: • as per customer orders? • Goods sent? • what feed back time? • Production figures: • after rejects • adjusted for loss / destruction in finished goods storage • business analysts must talk to everyone to ensure existence of reliable common methods

11. Reliable / Undisputed sources of data • Reliable mechanisms for data collection • No room for controversy RE basic figures of the business • Robust externally oriented systems for invoicing / paying • Robust measures of individual / area performance for the purpose of assessment and rewarding • Reliable systems for storage / processing / retrieval of data • Archiving

12. Corresponding Information Systems • The basic sub-systems are (see diagram): • payroll • order entry • inventory (goods for sales, raw material...) • shipping • accounts receivable • purchasing • receiving • accounts payable • general ledger Describe each sub-system’s missions

13. Part 2: Resources and constraints in Manufacturing environments • Goods are manufactured, not purchased • Demand must be counted or planned • Need RECIPES • activity must be planned for in advance • Resources must be allocated in advance • raw materials • Machine time • competent personnel (shift work) } limiting / constraining factors

14. Organisational Model • Driven by sales? • Driven by production? • Driven by marketing? • History of organisation and power structure determine which model is used • Plan dictates what volumes must be produced • Everything else follows from there Product matrix

15. Recipe or formula • How to produce our products • List of components including possible substitutes • How much of each • Special conditions of operation • Expected yields and labour productivity (i.e. standards) • Extrapolate a cost per unit • Stored in a Bill of Material (BOM)

16. Example: Bill of Material for desk 1 – List out the components 2 – describe the steps required for assembly 3 – arrange them in a possible manufacturing sequence

17. Solution Desk Top (1) Adjustable legs (4) Screw Kit (1) Frame (1) 3 way junctions (4) Painted tubing (4) Painted metal legs (4) Leg Tubes (4) Paint (0.6 dl) Long Tubes (2) Short Tubes (2) Paint (1 dl)

18. Capacity • Have limited capacity • Each unit of product requires a set time for each operation • Planning for capacity means analysing the requirement of all production runs for all products on all machines • Also, machines must be manned by operators • and machines have down time

19. Scheduling Manufacturing Tasks Based on desired production • determine quantities of RM to commit • schedule production runs (including sub-assemblies) • line up workers to operate the machines • Purchase required supplies This is called the Master Schedule

20. Master schedule • Issue for each week / day of production • aims at meeting the plan or the customers’ orders • allocate resources to all required activities • meeting of the key production people (end of week or Monday mornings). • Also review the problems with previous runs • Some computer systems are required for these tasks

21. Part 3: Data collection in the Factory • Computer Integrated Manufacturing (CIM) environments requires that companies: Know what they are doing • availability of data and quality of that data are key elements • many different types of data must be collected • procedures must be put in place • reliable • but not intrusive

22. Types of data • Volume data (production) • consumption data (raw material, packaging…) • personnel data • maintenance data • time related measurements • productivity data • All form the basis of the calculations used to monitor manufacturing activities

23. Type of data (2) • Primary data: • Secondary data or calculated data: • High level data:

24. Data for monitoring activities • Norm or budget is put together: • the more complete the model the more complete the monitoring • measurement methods and procedures are also put together • the structure of the budget tells you what data to collect

25. Data acquisition • Manual recording in a docket or other form (e.g. down time) • Sampling / testing of RM or products • collection and count of key part (e.g. shoulder blade) • scales for weight measurement- computerised or not • direct data entry in computer with infra-red beam (scanning) device (e.g. Dell) • remote electronic tracking • All these involve a trade-off between cost and accuracy and intrusiveness

26. Bad data recording • No data! • Too costly - e.g. in equipment or time • not timely – feed back too slow • inaccurate (e.g. procedure not well designed) • Lack of operator training / understanding • wrong incentive / instructions given • lack of control - open to dishonesty

27. Data storage • Series of ad-hoc systems manual and computer-based (spreadsheet, filed forms…) • Dedicated databases for manufacturing data (QC, shipping etc…) • Process Control Systems (technical parameters) • Other specialised proprietary systems • Entreprise Resource Planning (ERP) system

28. Using Manufacturing data • Operational data: • volumes - schedule / re-schedule runs • labour report - line up workers for next days • quality of output • Tactical data: • defect rates • productivity • Quality of RM • Strategic data: • product mix information • Market research • turnover of staff Some soft information is also required

29. Soft information • Data collection - • Grapevine • factory tours (talking and observing) • Data storage - • managers’ minds • special reports • Data usage: • ad-hoc basis • decision making

30. Part 4: Developing the Dashboard of information • Information cost • Information overload • Not all data can be / should be provided • Push versus pull model • For operational data => dashboard approach • Concept of control room • Analogy with process control or driving a car • Focus on most important factors

31. CSF - Theory • Definition: Limited number of areas where satisfactory results will ensure successful competitive performance for the individual, the department or the firm • Monitored on the basis of a set of measures - specific standards that allow the calibration of performance • Measures can be soft or hard - ie: objective or subjective

32. CSF method diagram • Identification of a hierarchy of performance measures that lead to identification of Critical Factors and Issues that will determine a business’ success The business mission statement The business vision statement multiple business goals multiple business objectives for each goal multiple CSFs for each objective

33. Implications for IS: multiple business objectives for each goal multiple CSFs for each objective Central Database - Data Warehouse Monitoring and Control Systems Dashboard Common Interface Indicators IS #1 IS #2 IS #3 IS #4

34. Sources of CSFs • Industry • Competitive strategy and industry position (leader / follower; big / small…) • Environmental factors (eg: economic fluctuations and national government policies) • Temporal factors (temporary CSFs) • Managerial position (more specific to one manager)

35. Classification of CSFs • Internal versus external • Monitoring versus Building / Adapting (eg: implementing of major corporate plan) • Evolution over time - eg: motor industry

36. + / - of the CSF technique • Small number of CSFs • Managers normally aware of them - make them explicit is possible • Specific to firm / dept / manager • But; not all CSFs are measurable at all (access to data) • Known CSFs may be trivial • Time consuming to go beyond the obvious • Will managers make time for CSF analysis?

37. Dashboards of information • A CSF analysis can be turned into a dashboard of info • indication in real time of what is happening • Concentration on the most important + visual impact (e.g. colour coding) • But data has to be very reliable and design of interface must be good : • three mile island

38. Some Problems with 3 mile Island • Layout of control not consistent with use of indicators • no consistency on where associated controls are situated or how they operated • layout of controls did not reflect layout of plant • indicators and alarms were not sorted by degree of importance • no consistency in use of colour • Cl: the layout of the dashboard and what indicators represent (+ how they do it) requires much attention

39. About dashboard development • Developing IS with decision making relevance is tricky • Nature of management work means difficult to imagine generic features • 1970 – 1980: focus on complex models borrowed from OR • Managers need simple systems that save them time

40. The Control Room • Monitoring complex processes through technology mediated systems • Controlling without seeing directly • Not directly applicable to management (human interaction component missing) • But useful anyway to measure performance in a more complete fashion

41. Key issues for dashboard development • Limited attention - selection of indicators (CSF) • Accurate performance measurement - methods used • Operator / user training - consensus / awareness • Dashboard layout - avoid confusion / be consistent

42. Framework for dashboard development Question 1: Who will use this indicator? Question 2: Can it be mapped out to a specific objective at a higher level? Question 3: How frequently will managers need to monitor it? Question 4: What calculation methods? What unit of measurement? Question 5: What data source exists? What should be created? Question 6: How detailed should the analysis be? How can the indicators be broken down? Question 7: What threshold values should be used to differentiate between adequate and inadequate performance? What comparisons can be made to assess the company’s performance? Question 8: How can it be represented for maximum visual impact? Question 9: What action must be taken when good or bad performance is measured? Question 10: How will it be monitored / archived in the long term Question 11: Is there any potential bias with the methods and data used for calculations? What incentives may be given to organizational actors? See handout

43. Example 1: Monitoring Maintenance • Imagine down time is increasing • don’t know enough to fix the problem (1) collect appropriate data on accidents: • maintenance staff time sheets • accident report for each problem - documented by operators • match both sources of data (2) store it in a suitable DB (3) analyse based on a number of CSF (4) present analysis in computer dashboard

44. CSF analysis for the maintenance • Number of accidents per run (per unit / product) • Nature of accident (several categories to be found) • Location of accidents • Average duration of repair (for each assembly line) • Average duration of repair for each staff? • Average duration of repair for each type of accident • Mapping of when accidents happen • establish thresholds

45. Location (% of all accidents) 5% al 1 10% W3 W3 Shipping 10% al 2 8% al 1 WP2 W2 W2 35% Stocks storage al 2 Main Corridor Finished 3% Goods al 1 WP1 W1 W1 6% cooling al 2 Changing 3 - 3 - 15% Other Areas: 2 % Rooms Stocks Preparation ovens and Related RM Quality Facilities Control

46. Time spent (% of down time) 5% al 1 5% W3 W3 Shipping 20% al 2 41% al 1 WP2 W2 W2 8% Stocks storage al 2 Finished Main Corridor 3% Goods al 1 WP1 W1 W1 4% cooling al 2 Changing 3 - 3 - 8% Other Areas: 2 % Rooms Stocks Preparation ovens and Related RM Quality Facilities Control

47. When accidents happen

48. Who does what?

49. Analysing the types of accidents

50. Conclusion on Maintenance • Can’t show everything • Data should be collected, but choices must be made for dashboard • Choices can be made based on: • scope for improvement • development VS monitoring (hierarchy of CSFs) • preferences of managers • Archives will show whether targets are achieved => new threshold values can be set