Capability analysis of assembly line production

Data processing: generic control systems or specific application – Specific application – apparatus or process – Product assembly or manufacturing

Reexamination Certificate

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C700S108000, C700S122000

Reexamination Certificate

active

06631305

ABSTRACT:

BACKGROUND OF THE INVENTION
This invention relates to a process for optimizing assembly line operations, and more particularly, to a process implementing certain aspects of the six sigma quality analysis program with lean production techniques to identify opportunities for improvement in assembly line production.
Traditional manufacturing processes often encompass single skilled operators, high work in process (WIP) inventories, constant expediting, and production schedule shuffling. These features add limiting effects, such as inefficiency in output, manpower, WIP inventories, and assembly line operations. Therefore, it would be desirable to utilize a process for evaluating and improving a manufacturing or assembly process.
Originally lean production was implemented in manufacturing or assembly line processes to overcome the problems associated with traditional manufacturing. Lean production was based on the Toyota manufacturing system and typical practices can be found in
The Machine that Changed the World
, by James P. Womack, 1991, Harper Collins Publishing Co. The basic philosophy of the lean production system is to manufacture in the most economical way possible. This is accomplished by focusing on meeting customer requirements, such as determining production time.
One of the key elements of lean production is producing to takt time. Determining takt time is an essential first step in analyzing an assembly line. Takt time is the rate in time that a plant must maintain to meet customer demand. One of the basic tenets of lean manufacturing is that if each operation is done in the same amount of time, e.g. at or below the takt time, then the result will be an efficient one-piece flow process. Control steps are often implemented to maintain continuous improvement in the assembly line. This is based on Kaizen techniques such as those found in
The New Manufacturing Challenge: Techniques for Continuous Improvement
, by Kiyoshi Suzaki, 1987, Free Press.
Typically in assembly lines these techniques based on takt time were used to balance the work of the individual operations and thus optimize the overall flow and efficiency of the assembly line. For example, all workstation operations or machines in a cell area produce to takt time to prevent over or under production. The following is an example of how takt time can be calculated where there are operations having 2 shifts per day, with 7.5 hours per shift, with 5 work days per week, and the demand of 150 pieces per week:
Takt time
=
Total Production Time Available
Demand
or Takt time
=
shift operation
×
7.5



hrs. per shift
×
5



days per week
150



pieces per week
such Takt time
=
0.5



hours or 30 minute
A lean production assembly line takt time analysis typically uses the average time in each operation of the process. However relying solely on the average values can result in missed opportunities for improvements in the assembly line or manufacturing process. Therefore, it would be desirable to efficiently obtain information on the variability and process capability of these operations to target missed improvement opportunities and to optimize process improvements. In part, there is a need for a more rigorous method than using average times for determining assembly line performance.
Six sigma methodology makes use of various statistical tools that workers and managers use to measure quality, both in development and production. One or more techniques can be used for the analysis and detailed illustrations of these techniques are found in
Implementing Six Sigma: Smarter Solutions Using Statistical Methods
, by Forrest W,. Breyfogle, III, 1999, John Wiley & Sons. These techniques include measurement validation techniques utilizing gage reproducibility and repeatability (gage R & R); variation analysis utilizing and standard deviation and mean; capability analysis utilizing process capability (CpK); improvement validation using confidence interval measurements; and determining primary goals such as those critical to quality (CTQ). However, these techniques have been primarily used to decrease product defects, which typically involved correcting product attributes that did not meet customer product quality requirements. Therefore, it would be desirable develop a new rigorous application implementing six sigma techniques, such as targeting opportunities for improvement in assembly line processes.
SUMMARY OF THE INVENTION
The present invention provides a process and means for identifying opportunities for improvement in assembly line production that overcomes the problem of overlooking opportunities for improvement. Six sigma techniques are used to identify these opportunities. The process includes collecting time data accurately representing operations in an assembly line; conducting a capability analysis of the data collected to identify opportunities for improving operations; identifying changes in operations based on this analysis; and implementing such changes into operations to produce improved assembly line performance.
One or more six sigma techniques used for identifying opportunities for improvement comprise gage R&R measurement validation; variation analysis utilizing mean values and standard deviation values; capability analysis utilizing process capability (CpK); utilizing confidence interval analysis; and implementing primary goals such as those critical to quality (CTQ).
The process of the present invention preferably utilizes a capability analysis comprising at least one of the following processes, analyzing overall process performance, analyzing individual operations in a process, predicting process performance, and serving as a basis for implementing steps in process optimization. In one aspect, the capability analysis of the operations comprises the calculation of the mean, standard deviation, process capacity (CpK), and a first set of confidence intervals obtained from the original assembly process, to identify system process time performance weaknesses, or defects. In another aspect, capability analysis comprises a second set of confidence intervals based on the assembly line after improvements are implemented to compare with the first set of confidence intervals obtained from the original data to validate improvements.
In yet another aspect, identifying changes in operations in an assembly line comprises improving those activities that yielded the highest operation data values in any given set of data to shift the process capability mean values lower than those originally obtained and to decrease the standard deviation values of that operation.
The process of the present invention preferably identifies opportunities for improvements in an assembly line comprising the steps of obtaining and validating takt time measurements using gage R&R analysis; conducting capability analyses on the overall process as well as each individual operation to determine opportunities for improvement; generating ideas to eliminate waste and improve performance through minimizing variability, balancing work of operations, and improving layout and flow; testing best ideas; implementing successes; documenting standard operations for controlling changes implemented; and repeating the cycle to maintain a continuous improvement flow.
The implementation of six sigma techniques gives the user flexibility to conduct rapid capability analysis of a process and implement improvements to ensure that each operation in an assembly process is at or below a specified takt time.


REFERENCES:
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patent: 5452218 (1995-09-01), Tucker et al.
patent: 5715181 (1998-02-01), Horst
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patent: 5956251 (1999-09-01), Atkinson et al.
patent: 6101826 (2000-08-01), Bessler
patent: 6184048 (2001-02-01), Ramon
www.tbmcg.com; Bob Dean “Defining Lean Sigma™”,Managing Times, 2nd Quarter 2001.
www.tbmcg.com Mark Oakeson, “Design for Lean Sigm

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