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Essay: Discussion of Problems with Data Analysis Tools to Improve Process Effectiveness

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5.0 Problem Solving

The data analysis tools are essential to effective process improvement because they help teams to find the solutions to end the problems. An effective system uses these instruments to produce value through process improvement. The following tools be used in this project for data analysis.  i) Pareto diagram  ii)  Why-Why analysis /Ishikawa diagram

Table 1. Finding The Root Causes &  a Determining Action Plan

NO Reasons Root Cause Action Plan

Production Losses

1 Unscheduled model entry F24 Improper planning can be disastrous. Flexible arrangement made in Assembly production line.

2 F24 fitment delay Improper supervision in working stage. Implementation of  Kan-ban to notify parts fitted.

3 CNG mounting delay Improper hoist maintenance. Weekly hoist maintenance, PM Chart.

4 Cabin low WIP in trim & paint Increased inspection time due to ineffectiveness in fitments. Supervision in each stage and Error proofing.

Shortage Losses

1 Gear box shortage Supply Issue

Often there is a sudden increase in demand Implemented flexibility in the organization and develop internal  vendors to have faster inventory management.

2 Material in perceived shortage its

3 Engine wiring harness shortage for  "x " module.

4 Propeller shaft shortage.

Quality  losses

1 Engine mounting insulator thread slippage Supply product issue. Proper inventory control, Six Sigma, Inspection of product quality.

2 F24 part quality issue Supply and demand issue Avoid unnecessary handling of the products in stores.

3 Power steering issue Lock nut thread washout

4 Brake booster part issue Thread washout in CCB clamping and Supply issue.

Machine losses

1 Brake oil Machine break down. Vacuum leak check fails due to the internal vacuum tank issue. History card implementation / PM Chart prepared.

2 The engine mounts are shot  

Motoring Lack of communication in the AEMS tackles due to heat generated in electronic devices Periodic maintenance and Machine Care.

10 min trial run before going.

Keep a check sheet.

Cut the unnecessary  movements.

3 Cab Under body tackle breakdown Hoist operation problem in up and down movement due to proxy fault

Table 2. Losses occur  during the Production, Shortage of parts, Quality and Machine

Loss No. of  Vehicles

1 Production Loss 2300

2 Part Quality 300

3 Part Shortage 920

4 Machine Breakdown 415

5 System Issues 172

6 IT Issue 250

7 Power Cut 15

Total 4372

5.1  Pareto Analysis  

A Pareto diagram is a diagnostic tool is used to share the quality loss. It is also called as 80/20 rule. It means only 20% of problems (defects) account for 80% of the effects. The Pareto analysis is executed for the losses mentioned previously and the graphs for every loss are as follows.

 

Figure 4.  Pareto analysis of Machine Breakdown

Figure 5.  Pareto analysis for Part Shortage

 

Figure 6.  Pareto analysis of part quality loss

 

Figure 7.  Pareto analysis of all losses

5.2  Cause and Effect diagram

  The technique is a diagram-based approach for thinking through all of the possible causes of a problem. This helps us to carry out a thorough analysis of the state of personal business.   Four steps are used to prepare the case and effect diagram

1. Identify the long term  crisis. 2. Work out the major factors involved.

3. Identify possible causes.   4. Analyze the diagram.

   

Figure 8.  Cause and effect diagram

6.  Data Analysis and OEE Calculation.

   Overall Equipment Effectiveness (OEE) has one of the important key indicators for measuring cause which widespread acceptance throughout the worldwide manufacturing industry. When we look closely the system that looks like the indicator of three reason performance, accessibility and quality output of the assembly line and systems, it perfectly matches with focused improvement processes such as TPM and Lean manufacturing. It helps raise awareness of degradation issues, identifies the spots with the improvement needs and provides feedback on the success of any continuous improvement measures. Data was collected for eight months for a calculation average value is calculated. The operation is of two shifts per day per shift excluding Sundays, the planned downtime per shift is 60 minutes during each shift for lunch and tea break.

Before

1) Total Target = 13088  Vehicles produced

2) Availability Loss =

=    Part shortage + Machine breakdown + IT Loss + Power cut

920 +415 +250+ 15 = 1600

3) Performance Loss =

= Production loss + IR  Issues

2300 + 175 =  2475

4) Availability =

= (13088-1600)/13088 = . 8777

87.77  %

5) Defects = 300 Vehicles

6) Performance = (Total target – Performance losses) / Total target

= (13088-2475)/13088

= 0.8108  =  81.08 %

7) Quality = (Output Quantity – Defective Quantity) / Output Quantity

= (9013-300)/9013 = 96.67%

8)   OEE = Availability x Performance x Quality

= 0.8777 x 0.8108 x 0.9667 0.6879  =  69.00 %

 After  Implementation

1) Total Target = 13088  Vehicles  produced

2) Availability Loss =

= Part shortage + Machine brakedown + IT Loss + Power cut

900  Vehicles

3) Performance Loss = Production loss + IR  Issues

4)  

Defect quantity =

= 980  Vehicles

100  Vehicles

5) Availability = (Total target – Availability losses) / Total target

=   (13088-900)/(13088)= 93.12%   

6) Performance = (Total target – Performance  losses) / Total target

= (13088-980)/13088 = 92.51%

7) Quality = (Output Quantity – Defective Quantity) / Output Quantity

= (11208-100)/11208 = 99.10 %

8) OEE = Availability x Performance x Quality

= 0.9312 x 0.9251x 0.9910   0.8532  =  85 %

7. Results and Discussions

Once the action plans are brought forward, they can be implemented to improve the productivity in the chassis assembly line by targeting the problems which create 80% of the effects. The outcome in a decrease in different loss is shown below.   

Figure 9.  Availability  losses  observed  after  OLE

   

 

   

   Figure 10.  Performance   losses  observed before   

 

Figure 11.  Performance   losses  observed after OLE

Figure 12. Quality   losses  observed  before

Figure 13. Quality   losses  observed  before OLE

In the assembly process has 85% efficiency and 15% losses. These losses, mainly are downtime losses, speed losses and quality losses which affect Overall Equipment effectiveness of the process. To cut these losses and to achieve world class OEE there should be a decrease in cases which are six big losses. The principal events which are responsible for losses in the fabrication process are available of Tools, Unplanned Maintenance Chart, Change over Time, Assembly Parts Shortages, Employee Shortages, Assembly layout, Improper Component Assembly. Organization need to subdue the non productive activities which are touching  the overall efficiency. They can contract by implementing the latest techniques and tools, proper inventory storage, in line assembly, skilled operator, special purpose machinery, etc. The progression in the overall line effectiveness before Implementation and after implementation of the action plan is shown in the below table.

 

Fig. 14  Comparison of OEE  Before and After

The Assembly line losses are countermeasure for chronic losses and bring back process, Part shortage, Machine breaks down, IT Loss and Power cut. By implementing TPM concept, autonomous maintenance and focused improvement and lean production concept  helps to cut the losses.

Table 3: OEE comparison between WCM and company

Company’s   Performance World – class Performance

95.83%  Availability >  90%  Availability

88.55% performance > 95% performance

99.9% rate of quality >  99% rate of quality

85%  OEE >   85% OEE

By this strategy performance of the assembly line  increased, reduces overall equipment maintenance cost, increase availability, productivity and quality improvement and employee morale.  OEE of the assembly line enhance from  69 to 85% help maximize throughput efficiency. The production problems into simple, intuitive presentation of information helps systematically improve processes with easy-to-obtain measurements.

8. Conclusions  

OLE is one of the key performance indicator tools for monitoring the effectiveness in the communication channel. This technique not only manages the assembly line, but also maintains and improves the line strength. The resulting due to carrying out of the action plans to the critical area in the assembly  line considerably reduces the losses and thus enhance the overall line effectiveness (OLE) in the Light Commercial Vehicle (LCV) chassis assembly line from 69% to 85 %. We learn from the Table 3  company achieves closer to world-class manufacturing company, quality loss, they applied strong quality measurement and inspection system from raw to end of the product inventory, but society has to work hard to improve their cars and trim the waste time.

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