1 Teaching Innovation - Entrepreneurial - Global The Centre for Technology enabled Teaching & Learning, N Y S S, India DTEL DTEL (Department for Technology Enhanced Learning)

DEPARTMENT OF COMPUTER TECHNOLOGY VIII-SEMESTER AUTOMATION IN PRODUCTION 2 CHAPTER NO.2 AUTOMATED INSPECTION AND GROUP TECHNOLOGY

CHAPTER 1:- SYLLABUSDTEL. Digital signal, Digital systems 1 Logic families- Characteristics, Classification 2 Number System- Classification 3 Basic gates 4 3 Boolean laws- De Morgan’s theorems 5

CHAPTER-1 SPECIFIC OBJECTIVE / COURSE OUTCOMEDTEL Understand the Digital Systems and Logic Families. 1 Conversion of different number systems The student will be able to:

DTEL Automated inspection 5 LECTURE 5:- AI & GT Inspection can be defined as the activity of examining the products, its components, sub-assemblies, or materials out of which it is made, and to determine whether they adhere to design specifications. Automated inspection is defined as the automation of one or more steps involved in the inspection procedure. Automated or semi-automated inspection can be implemented in the number of alternative ways. 100% inspection As in manual inspection, automated inspection can be performed using statistical sampling or 100% inspection. Sampling errors are possible when statistical sampling is used. Similar to human inspector, automated system can commit inspection error with either sampling or 100% inspection

DTEL Off-line Inspection 6 LECTURE 5:- AI & GT Off-line Inspection Methods In off-line inspection, the inspection equipment is usually dedicated and does not make any physical contact with machine tools 1. Variability of the process is well within the design tolerance, 2.Processing conditions are stable and the risk of significant deviation in the process is small, and 3.Cost incurred during inspection is high in comparison to the cost of few defective parts.

DTEL On-line Inspection 7 LECTURE 5:- AI & GT On-line/In-process and On-line/Post-process Inspection Methods If the inspection is performed during the manufacturing operation, it is called on-line/in-process inspection. If the inspection is performed immediately following the production process, it is called on-line/post-process inspection

DTEL Coordinate Metrology 8 LECTURE 5:- AI & GT Concerned with the measurement of the actual shape and dimensions of an object and comparing these with the desired shape and dimensions specified on a part drawing. Coordinate measuring machine (CMM) – an electromechanical system designed to perform coordinate metrology. A CMM consists of a contact probe that can be positioned in 3-D space relative to workpart features, and the x-y-z coordinates can be displayed and recorded to obtain dimensional data about geometry

DTEL Coordinate Measuring Machine 9 LECTURE 1:- AI & GT

DTEL CMM Components 10 LECTURE 1:- AI & GT Probe head and probe to contact workpart surfaces Mechanical structure that provides motion of the probe in x-y-z axes, and displacement transducers to measure the coordinate values of each axis Optional components (on many CMMs):  Drive system and control unit to move each axis  Digital computer system with application software (a) Single tip and (b) multiple tip probes

DTEL CMM Mechanical Structure 11 LECTURE 1:- AI & GT Six common types of CMM mechanical structures: 1.Cantilever 2.Moving bridge 3.Fixed bridge 4.Horizontal arm 5.Gantry 6.Column

DTEL CMM Structures 12 LECTURE 1:- AI & GT (a) Cantilever and (b) moving bridge structure

DTEL CMM Structures 13 LECTURE 1:- AI & GT (c) Fixed bridge and (d) horizontal arm (moving ram type)

DTEL CMM Structures 14 LECTURE 1:- AI & GT (e) Gantry and (f) column

DTEL Machine Vision 15 LECTURE 1:- AI & GT Acquisition of image data, followed by the processing and interpretation of these data by computer for some useful application Also called “computer vision” 2-D vs. 3-D vision systems:  2-D – two-dimensional image – adequate for many applications (e.g., inspecting flat surfaces, presence or absence of components)  3-D – three-dimensional image – requires structured light or two cameras

DTEL Operation of a Machine Vision System 16 LECTURE 1:- AI & GT 1.Image acquisition and digitization 2.Image processing and analysis 3.Interpretation

DTEL Image Acquisition and Digitization 17 LECTURE 1:- AI & GT With camera focused on subject, viewing area is divided into a matrix of picture elements (“pixels”)  Each pixel takes on a value proportional to the light intensity of that portion of the scene and is converted to its digital equivalent by ADC In a binary system, the light intensity is reduced to either of two values, white or black In a gray-scale system, multiple light intensities can be distinguished  Each frame is stored in a frame buffer (computer memory), refreshed 30 times per second

DTEL Dividing the image into a Matrix of Picture Elements (Pixels) 18 LECTURE 1:- AI & GT (a) The scene (b) 12 x 12 matrix superimposed on the scene (c) Pixel intensity values, either black or white, in the scene

DTEL Types of Cameras 19 LECTURE 1:- AI & GT Vidicon camera  Focus image on photoconductive surface followed by EB scan to determine pixel value  Have largely been replaced by Solid-state cameras  Focus image on 2-D array of very small, finely spaced photosensitive elements that emit an electrical charge proportional to the light intensity Smaller and more rugged No time lapse problem

DTEL Illumination Techniques 20 LECTURE 1:- AI & GT ( a) Front lighting, (b) back lighting, (c) side lighting

DTEL More Illumination Techniques 21 LECTURE 1:- AI & GT Structured lighting using a planar sheet of light

DTEL Image Processing and Analysis 22 LECTURE 1:- AI & GT Segmentation – techniques to define and separate regions of interest in the image  Thresholding – converts each pixel to a binary value (white or black) by comparing the intensity level to a defined threshold value  Edge detection – determines location of boundaries between an object and its background, using the contrast in light intensity between adjacent pixels at the boundary of an object Feature extraction – determines an object’s features such as length, area, aspect ratio

DTEL Interpretation 23 LECTURE 1:- AI & GT For a given application, the image must be interpreted based on extracted features Concerned with recognizing the object, called pattern recognition - common techniques:  Template matching – compares one or more features of the image object with a template (model) stored in memory  Feature weighting – combines several features into one measure by weighting each feature according to its relative importance in identifying the object

DTEL Machine Vision Applications 24 LECTURE 1:- AI & GT 1.Inspection:  Dimensional measurement  Dimensional gaging  Verify presence or absence of components in an assembly (e.g., PCB)  Verify hole locations or number of holes  Detection of flaws in printed labels 2.Identification – for parts sorting or counting 3.Visual guidance and control – for bin picking, seam tracking in continuous arc welding, part positioning

DTEL Other Optical Inspection Methods 25 LECTURE 1:- AI & GT Conventional optical instruments  Optical comparator  Conventional microscope Scanning laser systems Linear array devices Optical triangulation techniques

DTEL Scanning Laser Device 26 LECTURE 1:- AI & GT

DTEL Linear Array Measuring Device 27 LECTURE 1:- AI & GT

DTEL Optical Triangulation Sensing 28 LECTURE 1:- AI & GT Range R is desired to be measured Length L and angle A are fixed and known R can be determined from trigonometric relationships as follows: R = L cot A

DTEL Exercise – Convert LECTURE 1:- AI & GT

DTEL Exercise – Convert LECTURE 1:- AI & GT

DTEL Exercise – Convert LECTURE 1:- AI & GT

DTEL Exercise – Convert LECTURE 1:- AI & GT

DTEL 33 Off-line Inspection Methods LECTURE 3:- NUMBER SYSTEM

DTEL References Books: 34 References Web: