Process engineering

986
-1

Published on

Published in: Technology, Business
0 Comments
2 Likes
Statistics
Notes
  • Be the first to comment

No Downloads
Views
Total Views
986
On Slideshare
0
From Embeds
0
Number of Embeds
1
Actions
Shares
0
Downloads
27
Comments
0
Likes
2
Embeds 0
No embeds

No notes for slide

Process engineering

  1. 1. Process Engineering
  2. 2. Contents 3.0 Introduction 3.1 Experience-Based Planning 3.2 Decision Tables and Decision Trees 3.3 Process-Capability Analysis 3.4 Basic Machining Calculations 3.5 Process Optimization 3.6 Conclusion i-Design Lab.
  3. 3. 3.0 Introduction3.1 Experience-Based Planning3.2 Decision Tables and Decision Trees3.3 Process-Capability Analysis3.4 Basic Machining Calculations3.5 Process Optimization3.6 Conclusion i-Design Lab.
  4. 4. Introduction• Manufacturing • Raw material → Finished product• Process capability ismachine tools scientific knowledge for = historic and ?? each process (≠machine tools) historic Process Process Capability Scientific knowledge i-Design Lab.
  5. 5. Process Capability• Three levels of Process Capability Universal Shop Machine -level -level -level• Important parameters • The shapes and sizes • The dimensions and geometric tolerances • The material removal rate • The relative cost • Other cutting characteristics/constraints i-Design Lab.
  6. 6. 3.0 Introduction3.1 Experience-Based Planning3.2 Decision Tables and Decision Trees3.3 Process-Capability Analysis3.4 Basic Machining Calculations3.5 Process Optimization3.6 Conclusion i-Design Lab.
  7. 7. Experience-Based Planning"The accumulation of experience is knowledge "• Problem of Experience-Based • requires a significant period of time to accumulate • represents only approximate, not exact knowledge • is not directly applicable to new processes or new systems• Machinist Handbooks • has long been a standard manufacturing practice i-Design Lab.
  8. 8. 3.0 Introduction3.1 Experience-Based Planning3.2 Decision Tables and Decision Trees3.3 Process-Capability Analysis3.4 Basic Machining Calculations3.5 Process Optimization3.6 Conclusion i-Design Lab.
  9. 9. Decision Tables and Decision Trees • Describing the actions associated with conditions • Help systematize decision making • Translate each other • Difference • Ease and elegance of presentation and programming when a computer is used ConditionAction Stub Entries i-Design Lab.
  10. 10. Decision Table i-Design Lab.
  11. 11. Decision Table• When constructing, consider factors • Completeness, Accuracy, Redundancy • Consistency, Loops, Size• Merge Merge i-Design Lab.
  12. 12. Decision Table• Table splitting and parsing i-Design Lab.
  13. 13. Decision Tree• Single root, Node, Branch• Branch – ‘IF’, branches in series – ‘AND’ Node Branch Root i-Design Lab.
  14. 14. 3.0 Introduction3.1 Experience-Based Planning3.2 Decision Tables and Decision Trees3.3 Process-Capability Analysis3.4 Basic Machining Calculations3.5 Process Optimization3.6 Conclusion i-Design Lab.
  15. 15. Information Required to Make the Decision Shape Size LimitationCapability Tolerance Surface Finish Cutting ForceLimitation Power Consumption i-Design Lab.
  16. 16. Process Boundaries• One way to represent process capability• Limiting size, tolerances, surface finish• System-dependant i-Design Lab.
  17. 17. 3.0 Introduction3.1 Experience-Based Planning3.2 Decision Tables and Decision Trees3.3 Process-Capability Analysis3.4 Basic Machining Calculations3.5 Process Optimization3.6 Conclusion i-Design Lab.
  18. 18. Feed and Feed Rate• Feed • The relative lateral movement between the tool and the workpiece during a machining operation (= thickness of the chip) • Feed in turning and drilling • The advancement of the cutter per revolution of the workpiece (turning) or tool (drilling) • Unit - ipr (inch per revolution) • Feed in milling • The advancement of the cutter per cutter-tooth revolution • Unit - inch per revolution per tooth• Feed rate - ipm (inch per minute) • Equation (3. 17) i-Design Lab.
  19. 19. Machining• Cutting Speed • The maximum linear speed between the tool and the workpiece • Equation (3. 18)• Depth of cut • Width of the chip • Equation (3. 19)• Metal-Removal Rate • How fast material is removed from a workpiece • Equation (3. 20) ~ (3. 28) Short processing time MRR is Large ( ) Short the life of cutter i-Design Lab.
  20. 20. Machining Time• Total amount of time• Parameter • The length of the workpiece • Overtravel of the tool for clearance • The number of passes required to clear the volume• Equation (3. 29) ~ (3. 31) i-Design Lab.
  21. 21. Tool Life• Erosion (Wear) • Crater wear • High Temperature • Flank wear • Friction• Breakage (Catastrophic Failure)• F. W. Taylor • Tool-life Equation • Relation of Tool life and Cutting speed i-Design Lab.
  22. 22. Machining Force and Power Requirements• Important considerations in selecting process parameters (feed, speed, and depth of cut)• Not limiting values• Machining force • Equation (3. 35) ~ (3. 37)• Cutting power • Equation (3. 38) ~ (3. 39) i-Design Lab.
  23. 23. Process Parameters• Feed, Speed, Depth of cut• Process selection becomes an iterative procedure • Process Selection • Machining parameters are adjusted to accommodate the system constraints • Parameters affects the time and cost i-Design Lab.
  24. 24. 3.0 Introduction3.1 Experience-Based Planning3.2 Decision Tables and Decision Trees3.3 Process-Capability Analysis3.4 Basic Machining Calculations3.5 Process Optimization3.6 Conclusion i-Design Lab.
  25. 25. Process Optimization Short processing time MRR is Large ( ) Short the life of cutter• Tool has been worn → Replace• Trade-off between increased machining rate and machine idle time i-Design Lab.
  26. 26. Single-Pass Model• Assume that only one pass to produce the required geometry• The depth of cut is fixed• Constraint • Spindle-speed constraint • Feed constraint • Cutting-force constraint • Power constraint • Surface-finish constraint• Equation (3. 40) ~ (3. 47) i-Design Lab.
  27. 27. Multipass Model• Assumption of single-pass model is relaxed• Can be reconstructed into a single-pass model• The depth of cut is a control variable• Constraint • Spindle-speed constraint • Feed constraint • Cutting-force constraint • Power constraint • Surface-finish constraint • Depth-of-cut constraint• Equation (3. 63) ~ (3. 67)• No general solution method i-Design Lab.
  28. 28. 3.0 Introduction3.1 Experience-Based Planning3.2 Decision Tables and Decision Trees3.3 Process-Capability Analysis3.4 Basic Machining Calculations3.5 Process Optimization3.6 Conclusion i-Design Lab.
  29. 29. Conclusion• Information of process-planning system • Design knowledge – Chapter#2 • Process knowledge – This Chapter (Chapter#3)• Process planning • Procedure that matches the knowledge of the processes with the requirements of the design• Process Capability• Decision logic i-Design Lab.
  1. A particular slide catching your eye?

    Clipping is a handy way to collect important slides you want to go back to later.

×