Overall Line Effectiveness (OLE) is the Key Performance Indicator (KPI) to check the success in an organization by measuring availability, performance and quality. In a production job, whether it is assembly line or mass production organization followed the GEMBA technique that involves Quality, Cost Management, Critical Machines, Effective Ergonomics, 5s, Inventory and Safety. OLE improvement is one of the important practical tools for effective and efficient use available resources in any manufacturing sector. An OLE solution helps to work towards the world-class status. More specifically, it can extend benefits in important area equipment, people, process and quality. OLE evaluation is essential to determine the efficient production volume in a process layout and further give insight about where losses have taken place in that layout. From the plant operating time, we bear to cut down the planned closure, which includes all programs that should be excluded from efficiency analysis because of that location was no intention of passing production. One of the most significant indicators in the TPM philosophy is the Overall Equipment Effectiveness (OEE). The OEE indicator is a moment of the multiplication of three parameters which have a relevant function in the TPM. An OLE calculation begins with planned production time and scrutinize efficiency and productivity losses. They are downtime loss, speed loss and quality loss. For finding OLE, impact of Overall Effectiveness of product line, manufacturing system at the plant.
2.0 Problem Identification and Analyze
The assembly line is the manufacturing process where semi-finished parts move from one place to another station in the succession. With the process industry's integration of one cognitive process with another process is necessary to maximize the overall effectiveness of the assembly line than to center only on the efficiency of the single station operation parts. It is indispensable to improve the frequent breakdown of the machine, delay of assembly and delivery of product to the customer end. On the entire shop floor approach for mastering and enhancing of the Overall effectiveness, focused improvement and lean manufacturing concepts. Which serves to enhance OEE value of the assembly line. There is a very important for using metrics for the measurement efficiency.
3.0 Process Layout
Process layout is the trend of arranging the machines, equipment or ways in any continuous manufacturing line in a manner that the product will lead to the work arena in every particular. The layout is based along the critical time and shortest path considered.
Figure 1. Light commercial vehicle plant layout
For usage of the complete capacity of a continuous manufacturing line, the existence of several problems like Machine breakdown, Parts shortage, Forced line stoppage, synchronization of component loading and unloading time, Quality issue should be obsolete. Equally the society is delivering high demand of products, enhancing the run on the manufacturing line through implementing well developed and organized maintenance system helps to scrutinize the hidden elements, which hinders the capability of the existing business. We traced the journey of OLE path.
Figure 2. Journey of OLE implementation.
4.0 Data Analysis
Data analysis is a method of checking, sorting, placing and transforming data with the goal of finding the useful information and nagging data for making decisions. An indispensable part of insuring data integrity is the precise and proper analysis findings. Improper statistical analysis distorts findings and mislead casual readers. This investigation describes about the data analysis with the usage of different management tools, prioritizing the losses depending on their effects, calculation of the present system OLE in manufacturing line and the root causes of the problems with their proper action plans. In the graph, the problems that account for 80% of the effects are on the remaining side of the dotted vertical line. The losses are analyzed by Pareto diagram. Production volume data are essential for any calculation. The output volume is the amount of product that has been produced in a given time. The accompanying graph indicates the average daily yield for every week for the 4 months.
Figure 3. Histogram chart for production volume analysis
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.