The document discusses various types of sensors used for error-proofing techniques (Poka-Yoke), including: - Discrete and analog sensors - Presence sensors that require physical contact or are non-contact - Non-contact sensors like reed relays, inductive, capacitive, and photoelectric sensors It provides details on the advantages and applications of these different sensor types.

9. ERROR-PROOFING TECHNIQUES (Poka-Yoke) CONCEPT TYPES OF NON-CONTACT SENSORS: PHOTOELECTRIC SENSORS Conveyor Control This application involves sorting brown cardboard boxes which are coded with up to four black marks per box. The application is to sense the number of marks on each box. Package Handling A diffuse scan photoelectric control is used to detect the light reflected from the object in this application. The control detects the light reflected off the box, turning ON and OFF the gluing machine. Labeling This application is designed to detect the leading edge of a black bar code on a read and write label. The labels are edge to edge on a spool. When the bar code is detected the sensor output triggers a laser bar code reader which reads the bar code. Food Processing This application monitors the level of an accumulator in a meat processing facility. A photoelectric control detects a fill level of hot-dogs in the accumulator then turns on the conveyor for a preset time period. Side walls of the accumulator are polished stainless steel. The equipment is subject to daily washdown. Fill Level Control This application inspects the fill level of various jars of food products. The photoelectric system produces an output when either an under or over fill condition is detected. Parts Handling Fiber optics are ideal for areas too small for a standard photoelectric control. The fiber optic cables direct the light from the base to where the sensing is needed.

18. ERROR-PROOFING TECHNIQUES (Poka-Yoke) CONCEPT APPLICATIONS FOR PHOTOELECTRIC SENSORS

19. ERROR-PROOFING TECHNIQUES (Poka-Yoke) CONCEPT

21. ERROR-PROOFING TECHNIQUES (Poka-Yoke) CONCEPT POKA-YOKE Sensors at a Deming Prize Winner 1. Mechanical 9. Heat Sensor 2. Magnetic 10. Gas Sensor 3. Beam Cut 11. Force Sensor 4. Super Sonic 12. Torque Sensor 5. Image Sensor 13. Meter Relay 6. Counter 14. Vibration Sensor 7. Beam Reflector 15. Automatic Measurement 8. Pressure Sensor

23. ERROR-PROOFING TECHNIQUES (Poka-Yoke) CONCEPT EXAMPLES OF POKA-YOKE’S FOR THE THREE MOST COMMON PROBLEMS

24. ERROR-PROOFING TECHNIQUES (Poka-Yoke) CONCEPT What is the best method for sensing fluid levels for a machine? What is the best method for sensing magnets for electric motors? What are three possible methods for sensing burs on a cylinder bore? What is the best method for detecting the presence of an O-ring? BEST SENSING IDEAS

26. Missing Parts Is the part : Unseen or untouched in subsequent process steps? Difficult to see during assembly? Difficult to assemble? Difficult to see after assembly? Difficult to differentiate between pre and post assembly? Can anything be done to resolve this in design of product/process? Can the part be combined with another part? Can the part be eliminated? What can be done to detect whether the part has been assembled? Detection device - torque counter, photoelectric eye over container, limit switch at dispenser,.... Lock out subsequent operation if part is missing. Lock out device - limit switch, conductivity sensor... Implement operator instructions, visual aids and training as minimum requirement YES NO NO Implement Error Proofing (process/design change and/or detect/lock out device) Verify results YES

29. Misassembled Parts Is the part : Difficult to see during assembly? Difficult to assemble? Difficult to see after assembly? Difficult to differentiate between pre and post assembly? Lacking guides or fixtures for proper assembly or proper alignment? Can anything be done to resolve this in design of product/process? (guides, fixtures, automation) Can the part be combined with another part? Can the part be eliminated? What can be done to detect whether the part has been misassembled? Detection device - torque counter, photoelectric eye, limit switch Lock out subsequent operation if part is misassembled. Lock out device - limit switch, conductivity sensor... Implement operator instructions, visual aids and training as minimum requirement YES NO NO Implement Error Proofing (process/design change and/or detect/lock out device) Verify results YES

32. Incorrect Processing Does the operation require recognition of some characteristic to determine what to do with the part? (e.g. Red light indicates place in reject pile, visual inspection for pre-defined defects) Can anything be done to resolve this in design of product/process? (fixtures, automation) Can the part be combined with another part? Can the part be eliminated? What can be done to detect whether the part has been incorrectly processed? Detection device - reset button, photoelectric eye, limit switch Lock out subsequent operation if part is incorrectly processed. Lock out device - limit switch, conductivity sensor... Implement operator instructions, visual aids and training as minimum requirement YES NO NO Implement Error Proofing (process/design change and/or detect/lock out device) Verify results YES

35. Incorrect Parts Is there a selection of parts available at the workstation? Are similar parts assembled onto the product at the same location? Can anything be done to resolve this in design of product/process? (Consolidation, separate operations) Can the part be combined with another part? Can the part be eliminated? What can be done to detect whether the incorrect part has been assembled? Detection device - bar code, photoelectric eye, limit switch Lock out subsequent operation if the incorrect part is detected Lock out device - limit switch, conductivity sensor... Implement operator instructions, visual aids and training as minimum requirement YES NO NO Implement Error Proofing (process/design change and/or detect/lock out device) Verify results YES

38. 1% DEFECT RATE ( 99% YIELD ) OF ALL STATIONS RESULTS IN 78% CONFORMING PRODUCTS Cell 1 Cell 3 Cell 2 Cell 4 1% Defect Rate 1% Defect Rate 1% Defect Rate 1% Defect Rate 1% Defect Rate 1% Defect Rate 1% Defect Rate 1% Defect Rate 1% Defect Rate 1% Defect Rate 1% Defect Rate 1% Defect Rate 1% Defect Rate 1% Defect Rate 1% Defect Rate 1% Defect Rate 1% Defect Rate 1% Defect Rate 1% Defect Rate 1% Defect Rate

39. PROCESS FALLOUT TABLE Centered Process Process capability ratio Parts per million defective 0.50 133,600.00 0.75 24,400.00 1.00 2,700.00 1.10 967.00 1.20 318.00 1.30 96.00 1.40 26.00 1.50 6.80 1.60 1.60 1.70 0.34 1.80 0.06 2.00 0.0018

40. DIDN’T WASH HANDS

44. CASUAL CONNECTIONS BETWEEN DEFECTS AND HUMAN ERRORS Strongly Connected Connected SOURCE: NKS/Factory Magazine “Poka-Yoke” Causes of Defects Omitted Processing Processing Errors Errors Setting Up Workpieces Missing Parts Wrong Parts Processing Wrong Workpiece Misoperation Adjustment Error Improper Equipment Setup Improper Tools and Jigs Human Errors International Misunderstanding Forgeful Misidentification Amateurs Willful Inadvertent Slowness Non-Supervision Surprise