Consider the binary part-machine processing indicator matrix given in Fig. 1. Determine the machine groups and corresponding part families using: a) Rank Order Clustering (ROC) Algorithm; b) Direct Clustering Algorithm; c) Row and Column Masking (R & CM) Algorithm; d) Similarity Coefficient (SC) Algorithms; e) Also determine the dissimilarity coefficient matrix Fig. 1: Processing indicator matrix 2. Consider the binary part-machine processing indicator matrix given in Fig. 1. Determine the machine groups and corresponding part families using: Rank Order Clustering (ROC) Algorithm Direct Clustering Algorithm Row and Column Masking (R & CM) Algorithm Similarity Coefficient (SC) Algorithms Also determine the dissimilarity coefficient matrix Machine 4 5 1 2 3 6 7 1 2 3 4 5 6 7 1 - 1 - 1 - 1 - 1 - 1 - 1 1 - 1 1 - 1 - 1 - 1 1 1 1 1 1 1 1 1 - 1 1 - 1 1 - 1 1 1 - 1 1 1 - 1 Fig. 1: Processing indicator matrix
Added by Sean J.
Close
Step 1
- Rank the rows in descending order based on the sum. - Group the rows with the highest sum together, then repeat the process for the remaining rows until all rows are grouped. Show more…
Show all steps
Your feedback will help us improve your experience
Akash M and 53 other AP CS educators are ready to help you.
Ask a new question
Labs
Want to see this concept in action?
Explore this concept interactively to see how it behaves as you change inputs.
Key Concepts
Recommended Videos
24. Given the set of cluster labels and similarity matrix shown in Tables 7.15 and 7.16, respectively, compute the correlation between the similarity matrix and the ideal similarity matrix, i.e., the matrix whose ijth entry is 1 if two objects belong to the same cluster, and 0 otherwise. Table 7.15. Table of cluster labels for Exercise 24. Point Cluster Label P1 1 P2 1 P3 2 P4 2 Table 7.16. Similarity matrix for Exercise 24. Point P1 P2 P3 P4 P1 1 0.8 0.65 0.55 P2 0.8 1 0.7 0.6 P3 0.65 0.7 1 0.9 P4 0.55 0.6 0.9 1
Akash M.
Using the data below, compute the silhouette coefficient for each point, each of the two clusters, and the overall clustering. Cluster 1 contains {P1, P2}, Cluster 2 contains {P3, P4}. The dissimilarity matrix that we obtain from the similarity matrix is the following:
a) Use binary ordering heuristic to organize the machine-part incidence matrix. b) Use Production Flow Analysis (PFA) - Heuristic to propose a grouping of machines. Point out which groups must be visited by each product routing family.
Recommended Textbooks
Computer Science and Information Technology
Introduction to Programming Using Python
Computer Science - An Overview
Transcript
18,000,000+
Students on Numerade
Trusted by students at 8,000+ universities
Watch the video solution with this free unlock.
EMAIL
PASSWORD