Why to Develop Database for Learning Curve? (When You would not be Getting Repeat Order)

On the post "How to Calculate Production Target and Worker’s Bonus on Initial Days of Production Start?", I am asked this question, "Is there any benefit of developing a database in such case where style does not repeat?"

This is a good question. And you should also know why one should develop a database when there is no chance of getting repeat orders. In the following, I have briefly explained the benefits of creating a database. Though I have mentioned creating a database for the learning curve this thing is true for preparing the database for other areas too.

Based on Pareto's  principle (80-20 rule), you will find 80% similar operations in new styles, though you are not getting repeat order of a style (I am assuming that you will be working same product or similar product range). In production similar machines will be used to make the new styles - 80% machine will same as used in earlier styles. Also, most of your sewing operators are same. So, don't think that in new styles you will be doing something completely different things.

Create a database for daily efficiency figures (line efficiency as well as individual operator efficiency) for few styles during learning curve (initial days of production start of a style). If you look into the data you will find similar progress (trends) of efficiency after loading in most of the styles. 

If you go back to the post mentioned above, the purpose of making this database is to use for planning production target on the initial production days. And secondly planning incentive scheme for a worker on those days. You have no other way but referring past data to plan things in the initial days.   

Secondly, later at any point of time, you can look into the database for analyzing the performance of the line. The database can be used to compare with running orders. The comparison can be done in between sewing lines. By having the study of a longer period (suppose 6 months to one year) you can set your benchmark for the learning curve.
To get more precise data, you can make a separate database for each product. This data can be used for planning future orders.

Here developing database means recording day wise operator efficiency and line efficiency for the complete style run and then making a separate report for initial production days up to learning curve. You can also make trend chart for every style.

Learning curve: When a new style/product is loaded to a line, it reaches to maximum output after few days. As because on the initial days operator learn and build skill by doing job repeatedly. This duration is called learning curve. For example, the optimum output of a line is 500 pieces/day. 1st day it may produce only 100 pieces, 2nd day 250, 3rd day 450 and on 4th day onward it produces 500 garments. Same things applied to individual operators.

Prasanta Sarkar

Prasanta Sarkar is a textile engineer and a postgraduate in fashion technology from NIFT, New Delhi, India. He has authored 6 books in the field of garment manufacturing technology, garment business setup, and industrial engineering. He loves writing how-to guide articles in the fashion industry niche. He has been working in the apparel manufacturing industry since 2006. He has visited garment factories in many countries and implemented process improvement projects in numerous garment units in different continents including Asia, Europe, and South Africa. He is the founder and editor of the Online Clothing Study Blog.

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