Production Scheduling: location of the user in the decision-making architecture

1. Production Scheduling: location of the user in the decision-making architecture Peter G. Higgins

2. Outline • Standard scheduling software • features • design criteria • Real scheduling environment • Decision Architecture • Cognitive Work Analysis

3. Heuristic produces sequence

4. Scheduling Rules GANTT CHART Timing at resources Performance prediction Standard Decision Architecture

5. Normative Design Criteria • Operations Research Model • few attributes • due date • processing time • Goals • maximise resource utilisation • minimise tardiness • Heuristics • tendency to meet goals for simple problems • all jobs available • single resource

6. Real Scheduling • Complex • especially job shops • Uncertainties • job arrivals, material availability, processing & set-up times • Perplexity • multiple goals • conflict • importance varies

7. Standard Solution for Mismatch between Design Model and Reality • Human moves jobs using mouse

8. Decision Architecture for Real Environments • Locatehuman activity centrally in the decision-making process • computer: data representation, heuristics, rules • Use Cognitive Work Analysis to analyse the work domain and decision-making activities in complex systems in which there are many competing and conflicting goals. • Use theories of signification to inform interface design.

9. Knowledge-Based Adviser Scheduling Rules GANTT JOBS CHART WINDOWS Timing at resources Performance Unassigned prediction Sequence Job attributes Machine 1 Sequence Job attributes HUMAN DECISION MAKING Context Setting Pattern Recognition Machine n Sequence Job attributes Decision Architecture

10. Resource’s Weighted Tardiness Net Weighted Tardiness Weighted Tardiness Tardiness

11. Time constraint on Due date

12. Earliest Due Date Due Date

14. Visible on double clicking Visible on double clicking Detailed data in pop-up

15. Complexity and Perplexity of the Real Domain • Apply Cognitive Work Analysis

16. Ends Physical Function Physical Device Means

18. Goal: Low press set-up time Identify set of jobs requiring current major set-up Scan available jobs Activity Analysis #1

19. Low press set-up time Particular jobs meet their due date Many feasible goals Activity Analysis

20. Goal Structure Maximise short-term financial viability Maximise productivity Fully utilise all machines Low press set-up time Low press idle time

21. Goal Structure

22. Goal structure used to design DSS Visualisation: performance of higher level goals Human normally operates with these goals Visualisation of measures of performance

24. Printing example shows the complexity

26. Benefits of this approach • The pursuit of goals and enforcement of constraints that are difficult to represent computationally • The following of methods that schedulers find natural • The freedom for schedulers to use their intuition

28. earliness weight tardiness weight tardiness

30. Constraints differ between abstraction hierarchies

32. AI model • Constraint satisfaction • simulation • problem of rule management • made-to-order or customised • expensive • difficult to maintain