cim report

By, Deepak Chandran A20336465 Kaivalya Chaturvedi A20335367 Praveen S R A20325931 Prasanna Venkatesh Ramkumar A20338828 Rahul Garg A20334391 Saurabh Dhuri A20325517

CONSULTING PROJECT REPORT

MMAE 557: Computer Integrated Manufacturing- Systems

Course Instructor: Prof. John C. Cesarone

I

Table of Contents 1) Client Description ............................................................................................................................ 1

1.1) About the factory/operations .................................................................................................. 1 2) Analyze the client ............................................................................................................................ 3 3) Optimization of System ................................................................................................................... 4

3.1) Optimum number of workstations ........................................................................................... 4 3.2) Motion Study Analyses .............................................................................................................. 6 3.3) Analyzing after implementation of new system ....................................................................... 8

3.4) Machine Cluster Analyses ......................................................................................................... 9

3.5) Cost Analyses with Machine Cluster ....................................................................................... 10

4) Automation of System ................................................................................................................... 11

5) Quality Assurance and Inspection ................................................................................................. 13

5.1) Statistical Process and Quality Analyses ................................................................................. 13

5.2) Inspection Analyses ................................................................................................................. 18

CHAPTER 1 CLIENT DESCRIPTION:

Our client is KCP technologies Private Ltd, Goa, India. A firm that makes screw pumps rotors for South Asian pump manufacturers like ROTO, Flowserve, Netzsch etc. Their products cater pumping solutions for handling complex fluids in food, chemical, oil and gas, waste water, renewable energy and further more industries. In the recent times, they are looking forward to adapt the latest manufacturing methods or production management tools which would improve their current profit margin without investing much on technological changes. As a result, we have been appointed as a CIM consultant to audit, analyze and optimize their present system. This report will serve as a basis for future expansion and construction of new optimized plants across the country. 1.1 About the factory/operations:

• The factory consists of 3 CNC workstations, 4 full time workers and 1 utility worker. There is a loading and unloading bay where raw materials are transported into and out of the workshop through crates in forklifts. Each workstation has a tool table, job table where they next part to be loaded is stacked and finished product stock where the finished part is kept. Upon completion of the manufacturing process, the utility workers transport the parts to the inspection table where a worker inspects the finished products with their corresponding part drawings. A basic layout of the factory is sketched for further understanding.

• They significantly make 2 models of screw pump rotors in a batch production process. The batch size is normally decided to meet the current demands of their client. The list of activities within the CNC are facing, turning, taper turning, knurling, grooving, drilling and whirling.

• According to the classifications of various manufacturing systems, this factory belongs to ‘Type I M B’. Type I M states that it works on single station manned cell and B indicates that the cell produces rotors in batch production system.

PLANT LAYOUT

CHAPTER 2 ANALYZE YOUR CLIENT: Our client manufacturers 5050 screw pump rotors (on average) for every financial year in 2 batches. Among this, 3200 units are rotor A and 1850 units are Rotor B. By constant observations of the machining activities of the workers in the CNC lathe, we have recorded machining time for 5 samples of Rotor A and 5 samples of Rotor B using stop watches in order to deduce the average cycle time and thereby calculate the average production rate of each product.

Machining Activity

Rotor A Rotor B 1 2 3 4 5 Avg. 1 2 3 4 5 Avg.

Unload & Load next part 2.70 2.30 2.00 3.00 2.50 2.5 3.00 3.00 3.00 3.50 2.50 3 Unload & Load next tool 7.50 7.50 7.60 7.70 7.20 7.5 8.00 8.00 7.50 7.80 8.70 8 Part program checking 1.00 1.00 1.00 1.00 1.00 1 1.00 1.00 1.00 1.00 1.00 1 Facing 2.95 3.05 3.00 2.90 3.10 3 4.95 5.05 5.10 5.15 4.75 5 Turning 6.50 6.50 6.25 6.45 6.80 6.5 8.55 8.50 8.45 8.40 8.60 8.5 Taper turning 3.90 4.00 4.00 3.95 4.15 4 6.00 6.00 6.15 5.90 5.95 6 Grooving 3.50 3.55 3.40 3.40 3.65 3.5 4.50 4.55 4.45 4.40 4.60 4.5 Knurling 4.00 3.90 4.10 3.95 4.05 4 3.50 3.50 3.55 3.55 3.40 3.5 Drilling 5.50 5.35 5.40 5.65 5.60 5.5 6.90 6.85 7.15 7.05 7.05 7 Whirling 10.40 10.70 10.25 10.50 10.65 10.5 16.50 16.45 16.55 16.60 16.40 16.5 Average Cycle

time (min/part)

48 63

Production rate (Rp) = 60 / Tc Average Cycle time for rotor A (Tc) = 48 min Average Cycle time for rotor B (Tc) = 63 min This implies,

Production rate (A) [parts/hr] = 1.25. Production rate (B) [parts/hr] = 0.95.

CHAPTER 3 OPTIMIZATION OF SYSTEM: After a thorough study and analysis of the present system, we have worked on the following parameters for optimization of the current process of the manufacturer:

1. Evaluating the optimum number of workstations for the present work scenario. 2. Application of motion-study and thereby reducing the repositioning time of the

active workers. 3. Formulating the possibilities for combining to a machine cluster.

3.1- Optimum number of workstations: For evaluating optimum number of workstations, we have assumed the following data from the various sources: Parameter Unit Quantity Source of data Units produced Parts/hr Q(A) - 3200 Average values taken from the financial

report of company for the past 5 years. Q(B) - 1850 Cycle time min Tc(A) – 48 Average value taken form the series of

sample machining time. Tc(B) – 63 Scrap rate % µ(A) – 3 Average scrap produced by client for each

rotor. (obtained from client’s end) µ(B) - 7 Worker efficiency during operation % α – 92

Values measured/ assumed from client’s end based on their current manufacturing scheme.

Reliability during running % β – 90 Reliability during setup % γ – 95 Setup time min T(sp) - 45

Average Batch size parts N - 20

On reviewing the annual sales reports for the past 5 years, it said that there is an average changeover from Rotor A to B for every 20 rotors produced. Therefore, we may assume 20 as our batch size as instructed by our client.

Factory Operating hours: Hours/day (h/d) = 8. Days/week (d/wk) = 5. Weeks/year ( wk/yr) = 50.

Workload (A) = WL(A) = Q(A) * Tc (A) = 3200 * (48/60) (1- µ(A) ) (1 - 0.03 ) = 2639.17 hours/yr Workload (B) = WL (B) = Q(B) * Tc (B) = 1850 * (63/60) (1- µ(B)) (1 - 0.07 ) = 2088.71 hours/yr Available time (AT) = 8 * 50 * 5 = 2000 hours/yr No. of setup changes = Q (A) + Q (B) = 3200 + 1850 N 20 = 252.5 Workload (setup) = WL (sp) = No. of setup changes * T(sp) = 252.5 * (45/60) = 189.375 hours/ year Optimum number of workstations = WL (A) + WL (B) + WL (sp) AT * α * β AT * γ = 2639.17 + 2088.71 + 189.38 2000 * 0.9 * 0.92 2000 * 0.95 = 2.88 + 0.09 = 2.97 Since there are currently 3 workstations, the system already has the optimum number of workstations. Also, utilization factor is 99% so there is no possibility of overtime work. The factory are presumed to meet their sales with the current number of workstations.

3.2- Motion Study Analysis: The factory uses primitive CNC machines which can hold only 4 tools in its tool gallery. Therefore there will be regular movement of worker between the CNC lathe and tool table in order to place the right tools for the right object as per the part program. Keeping this factor in mind, a motion study analysis was conducted. The sole aim of the study was to provide workers close proximity to the tools they frequently use thereby reducing their travel time by making a few modifications in the system layout.

Apart from the layout changes, the tools in the tool table are recommended to be classified according to their application and placed on the adjacent wall nearby the CNC machine.

Travel within workstations Frequency Distance w.r.t Old layout

Distance w.r.t Proposed layout

Tool Table to CNC 4 4 1 Job stock to CNC 2 4 3.5 Finished products stock to CNC 2 5.5 3.5

Total Distance covered by worker/ part produced 35 18 Travelling distance will be reduced by (m) = 17 Average human walking speed (m/min) = 33.33 Time saved as per proposed layout in walking = 17/33.33

= 0.51 min Time saved in reorganizing tool table and placing tools as per standard ergonomic ways with proper classification 0.5 min

Total time saved by motion study will be close to 1 min.

Existing cutting tool and job arrangement Proposed classified arrangement

Same is applicable in the case of hardware and spanners. This also reduces time in fixing and aligning the parts in the CNC. Existing hardware arrangement Proposed hardware arrangement

3.3- Analyzing after implementation of new system layout:

Machining Activity

Rotor A Rotor B 1 2 3 4 5 1 2 3 4 5 Avg

Unload & Load next part 2.70 2.30 2.00 3.00 2.50 2.5 2.80 2.50 3.20 3.00 3.50 3 Unload & Load next tool 6.50 6.50 6.60 6.70 6.20 6.5 7.10 7.00 7.20 7.00 6.70 7 Part prog checking 1.00 1.00 1.00 1.00 1.00 1 1.00 1.00 1.00 1.00 1.00 1 Facing 2.90 3.10 3.00 3.00 3.00 3 5.00 4.70 5.10 4.80 5.40 5 Turning 6.40 6.60 6.20 6.40 6.90 6.5 8.20 8.80 5.50 8.10 8.90 8.5 Taper turning 3.00 4.10 4.00 4.00 4.10 4 6.60 5.90 6.10 5.80 5.60 6 Grooving 3.60 3.40 3.50 3.10 3.90 3.5 4.40 4.60 4.30 4.50 4.70 4.5 Knurling 4.00 4.00 4.00 4.00 4.00 4 3.00 3.20 3.50 4.00 3.80 3.5 Drilling 5.60 5.25 5.30 5.75 5.60 5.5 7.40 6.30 7.10 7.70 6.50 7 Whirling 10.20 10.90 10.20 10.40 10.70 10.5 16.60 16.40 16.00 16.80 16.70 16.5 Average Cycle

Time (min/part)

47 62

Production rate (Rp) = 60 / Tc Average Cycle time for rotor A (Tc) = 47 min Average Cycle time for rotor B (Tc) = 62 min This implies,

Production rate (A) [parts/hr] = 1.28. Production rate (B) [parts/hr] = 0.97. Naturally, the production rates have improved.

3.4- Machine Cluster Analysis: We have already optimized the repositioning time of workers by introducing organizational changes and rearrangement of tables. In this section, we have checked the possibility for formation of the cluster arrangement since we are using CNC lathes in a semi-automatic operation. For Rotor A: Machining time (Tm) = 38 min Worker setup time (Ts) = 9 min Repositioning time (Tr) = 2 min No. of machines which can be handled by 1 worker = Tm + Ts Ts + Tr = 38 + 9 = 4.27 9 + 2 For Rotor B: Machining time (Tm) = 52 min Worker setup time (Ts) = 10 min Repositioning time (Tr) = 2 min No. of machines which can be handled by 1 worker = Tm + Ts Ts + Tr = 52+ 10 = 5.17 10 + 2 This concludes that even while manufacturing rotor A or B, the complete machining operation can be managed by a single worker.

3.5- Cost Analysis with Machine Cluster: Production Cost / Unit as per present situation : Labor Cost (CL) 7.5 $/hr Machine Cost (CM) 25 $/hr No. of labors assigned 3 No. of Machines 3 Cost per unit = Tc * (CL + CM) / 60 Rotor A Rotor B Cost per unit ($) 26 34.13 Production Cost with respect to our recommendations ( Cluster) : Labor Cost (CL) 15 $/hr Machine Cost (CM) 25 $/hr No. of labors assigned (NL) 1 No. of Machines 3 Cost per unit = Tc * (CL / NL + CM) / 60 Rotor A Rotor B Cost per unit ($) 23.5 31 For both products, there is a savings in production cost required. Thus, we propose our cluster arrangement is economical even though the labor wage is doubled.

CHAPTER 4 AUTOMATION OF SYSTEM Considering the manufacturing system has an optimized process, analysis is further going to be conducted on the feasibility on automating the process. The different areas that can be automated are:

1. Machining operation. 2. Material handling and transport 3. Inspection.

Since, the factory is already operating with CNC machines where the worker attention is required only for some time within the machining cycle, we are not further investigating into this. On a detailed study of the plant layout, we feel that the there is more scope in automation of material handling and transport with the help of a conveyor belt which loops through all the workstations, inspection desk and loading & unloading bay. This conveyor belt intermittently operates and is manually overridden by a push button station near the conveyor belt. The part moves around the conveyor only during their cycle time. This will reduce time synthesized for material handling, part loading and unloading operations and transport of finished products to the inspection desk. Additionally, the space required for storage of job and finished products can be reduced as same will be taken care by the conveyor.

4.1- Analyzing after implementation of conveyor:

Machining Activity Rotor A Rotor B 1 2 3 4 5 Avg 1 2 3 4 5 Avg

Unload & Load next part 1.60 1.80 1.30 1.20 1.60 1.5 1.60 1.80 1.30 1.20 1.60 1.5

Unload & Load next tool 6.30 5.90 6.70 6.60 7.00 6.5 6.80 6.40 7.20 7.10 7.50 7

Part prog checking 1.00 1.00 1.00 1.00 1.00 1 1.00 1.00 1.00 1.00 1.00 1 Facing 2.80 2.70 3.50 3.20 2.80 3 4.80 4.70 5.20 5.30 5.00 5 Turning 6.20 6.00 5.90 6.80 7.60 6.5 8.50 8.20 8.80 8.10 8.90 8.5 Taper turning 4.20 3.70 3.90 4.30 3.90 4 6.60 5.90 6.10 5.80 5.60 6 Grooving 3.40 3.80 3.10 3.50 3.70 3.5 4.40 4.60 4.30 4.50 4.70 4.5 Knurling 4.20 3.70 3.90 4.30 3.90 4 3.40 3.80 3.10 3.50 3.70 3.5 Drilling 6.00 5.10 5.40 6.10 4.90 5.5 6.50 6.30 7.40 7.10 7.70 7 Whirling 10.20 10.10 10.80 10.30 11.10 10.5 16.60 16.40 16.00 16.80 16.70 16.5

Average Cycle Time (min/part) 46 60.5

Production rate (Rp) = 60 / Tc Average Cycle time for rotor A (Tc) = 46 min Average Cycle time for rotor B (Tc) = 60.5min This implies, Production rate (A) [parts/hr] = 1.31. Production rate (B) [parts/hr] = 0.99. This proves that there this an increase in production rates for both the models of rotors produced by the factory through installing a conveyor system. This may also remove the need of utility workers as transport of rotors are controlled by the workers.

CHAPTER 5

QUALITY ASSURANCE Quality inspections are the essential part of any manufacturing industry. Routine inspections are typically conducted as a daily, weekly, monthly or yearly quality inspection audit that may be focused on worker productivity as well as the quality of a finished product such as a manufactured toy or piece of clothing. Quality inspection objectives vary depending on the company's primary objective, but most quality inspections are designed to promote business profitability. The main intention is to check whether the part or assembly is made exactly or close to what it’s designed for. The quality assurance technique presently followed by the company are very traditional. They inspect all the rotors produced everyday manually. Vernier Calipers are used to inspect the two outer diameters of the rotor at various locations. Holes, grooves, and tapers are also measured manually with basic instruments. These were compared with the measurements in the part drawings visually. If the measurements are within tolerance they were shipped to their client else it was sent for rework or scrap. The profile of the mid-section profile and helical angle was not inspected. Before, checking importance of inspection for the client we have analyzed whether the process is in statistical control. 5.1- Statistical Process & Quality Analysis: Statistical process control involves the use of various methods to measure and analyze a process. Control charts have been used to check whether the process of the company is under statistical control. The purpose of the control chart is to identify when the process has gone out of statistical control. For evaluating the above analysis, • The mean and the range charts are plotted with sample number(S) in the x-

direction and the mean and range of the dimension of the rotor diameters measured at 5 different points in the y- direction.

• Sample size of 5 is taken to plot the charts (n=5) and (m=8). • The charts are plotted for both Rotor A (2 inch) and Rotor B (2.5 inch).

1. chart for Rotor A: Sample Measures Mean(CL) UCL LCL

2.002 2 2.014520921 1.985479079 2.004 2 2.014520921 1.985479079 1.998 2 2.014520921 1.985479079 2.001 2 2.014520921 1.985479079 1.995 2 2.014520921 1.985479079 1.993 2 2.014520921 1.985479079 2.008 2 2.014520921 1.985479079 1.999 2 2.014520921 1.985479079

1.971.975

1.981.985

1.991.995

22.005

2.012.015

2.02

1 2 3 4 5 6 7 8

Sample MeasuresMean(CL)UCLLCL

3σ

3σ

Sample number

Dimension

2. Range chart for Rotor A:

Sample Measures Mean(CL) UCL LCL 0.009 0.018 0.036 -0.001 0.024 0.018 0.036 -0.001 0.011 0.018 0.036 -0.001 0.014 0.018 0.036 -0.001 0.020 0.018 0.036 -0.001 0.017 0.018 0.036 -0.001 0.027 0.018 0.036 -0.001 0.018 0.018 0.036 -0.001

-0.0050.0000.0050.0100.0150.0200.0250.0300.0350.040

1 2 3 4 5 6 7 8


3σ

3σ

Sample number

Range

3. chart for Rotor B:

Sample Measures Mean(CL) UCL LCL 2.501 2.500 2.511 2.490 2.503 2.500 2.511 2.490 2.497 2.500 2.511 2.490 2.504 2.500 2.511 2.490 2.496 2.500 2.511 2.490 2.498 2.500 2.511 2.490 2.505 2.500 2.511 2.490 2.499 2.500 2.511 2.490

2.480

2.485

2.490

2.495

2.500

2.505

2.510

2.515

1 2 3 4 5 6 7 8


3σ

3σ

Sample number

Dimension

4. Range chart for Rotor B: Sample Measure Mean(CL) UCL LCL

0.01 0.009375 0.02371214 -0.00496214 0.012 0.009375 0.02371214 -0.00496214 0.006 0.009375 0.02371214 -0.00496214 0.014 0.009375 0.02371214 -0.00496214 0.003 0.009375 0.02371214 -0.00496214 0.005 0.009375 0.02371214 -0.00496214 0.017 0.009375 0.02371214 -0.00496214 0.008 0.009375 0.02371214 -0.00496214

With reference to the samples we have analyzed, the process seems to be in statistical control and is found to be stable. However, defect rates may be found due to the variability in machining operations.

-0.01

-0.005

0

0.005

0.01

0.015

0.02

0.025

0.03

1 2 3 4 5 6 7 8

Sample MeasureMean(CL)UCLLCL

3σ

3σ

Sample number

Range

5.2- Inspection Analysis: As mentioned earlier, there are many variables associated with the manufacturing processes. In order to keep up with client’s requirement, products are manufactured in excess. We have considered the defect rates in the manufacturing operations to find out whether the present production rate can meet up the client’s annual requirement i.e., 3000 units of Rotor A & 1750 units of Rotor B. Effect of defect rate in a series production Since the diameters are always in statistical control and the helical profile of the rotor have not been inspected. The probable defects that the parts experience could be from drilling or whirling operation. Taking this into consideration, we have analyzed whether the current production scheme would be able to meet the client requirements. Let Qo be the quantity of parts produced and q be the defect rates of the machining operation. Good products (Q) = Qo x (1-q) Defected products (D)= Qo x q Q = Qo (1-q1) (1-q2)........................ (1-qn) [When there is a series of ‘n’ operations in the products & q is their corresponding defect rates] For Rotor A: Qo = 3200 n = 2 q= 0.03 (Manufacturer’s standard) Qo= 3200 (1-0.03)2

So, Qo = 3010 which is greater than 3000. For Rotor B: Qo = 1850 n = 2 q = 0.0275 Q0 = 1850 (1 - 0.0275)2 So, Qo = 1758 which is greater than 1750. Hence, with the assumed defect rates they should meet their client demands.

Despite the above conclusions, we have received and reviewed several reports which have been provided from client’s inspection. These commonly state that there pump rotors do not rub the stators of the screw pump with optimum rubbing velocity and this had decreased the performance of the pumps. Thus we recommended the company to send random samples of part A and part B to a third party inspection contractor who uses a multi touch probe cantilever coordinate measuring machine to inspect the profile of the rotor and it was found out that the number of defects had increased as follows: Part A had 5 defects out of 23 parts. Part B had 3 defects out of 17 parts. This action helped the company improve on their quality check. They decided to send random samples of rotors to a third party Inspection Company who regularly checks for any deviations in the helical profile and provide necessary suggestions for preventing the same in machining on a weekly basis. M/s KCP felt this was an effective way in understanding their variability based on the feedback received. Additionally, the company considered in purchasing a CMM in future expansion of the plant. Further recommendations for improved quality:

� We suggest to buy a test rig prototype of the pumps that use these rotors and conduct dye penetration tests to analyze the contact region between stator and rotor.

� Once the factory has well expanded, several clusters can be grouped. Pick and place robots facilitated with tongs, could be considered to handle parts efficiently and same could be supported with an automatic pallet changer to reducing the repositioning time spent on part handling. For a large volume of production this would certainly help in reducing the cycle time despite the investment.

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