W9_TRI_ Blog Posting Learning Curve

1.      Problem recognition, definition and evaluation

Blog Posting is a weekly assignment to be done by team member. After posting 8 weeks of blog, the actual data is presented in Table 1 below. By applying learning curve theory, how much time will it need to write a posting blog in week 24?

Table 1.  Actual Blog Writing Duration

Week	Title	Writing (Minutes)	Average (Minutes)
1	Mahakam13 Team Stage	90	90.0
2	Paper Topic-1 Force Field Analysis	80	85.0
3	Paper Topic-2 Force Field Analysis	80	83.3
4	Paper Topic Force Field Final	80	82.5
5	Paper Topic Non Compensatory Model	75	81.0
6	Paper Topic Compensatory Model	75	80.0
7	EPCI Payment Term & Tender Price	80	80.0
8	Billet Price and Gold Equivalent	70	78.8

2.      Development of the feasible alternative

The concept of the learning curve was introduced to the aircraft industry in 1936 when T. P. Wright published an article in the February 1936 Journal of the Aeronautical Science. The learning curve method is basically based on concept where [input resources] reduce on [per output unit] basis as [number of units produces] increases. The formula of learning curve is shown as follows:

Z (u) = K * uⁿ

n = log (S) / log (2)

Where,

Z = estimated unit time u

K = unit for production time 1

S = efficiency / improvement / learning rate

3.      Development of the outcomes

Using those equations, Table 2 and Figure 1 describes the learning process, where K = 90 and S = 90%.

Table 2. Learning Curve Calculation

Week	Unit Time (Min's)	Average Time (Min's)
1	90.00	90.0
2	81.00	85.5
3	76.16	82.4
4	72.90	80.0
5	70.47	78.1
6	68.54	76.5
7	66.96	75.1
8	65.61	74.0
9	64.45	72.9
10	63.42	72.0
11	62.51	71.1
12	61.69	70.3
13	60.94	69.6
14	60.26	68.9
15	59.63	68.3
16	59.05	67.7
17	58.51	67.2
18	58.00	66.7
19	57.53	66.2
20	57.08	65.7
21	56.66	65.3
22	56.26	64.9
23	55.88	64.5
24	55.52	64.1

Figure 1. Learning Curve of Blog Posting

Furthermore, the learning process can be also analyzed using trend line concept using Ms Excel. Figure 2 presents the data and trend line curve, in which equation used is logarithmic.

Figure 2. Learning Curve using Trend Line

4.      Criteria of Selection

Using trend line, the selection of equation is based on R-squared number that represent how fit the equitation plotted to existing data. Table 2 presents learning curve calculation using trend line method.

Table 2. Learning Curve Calculation using Trend Line

	Trend line Writing Duration	R Squared	Est. Week 24 (Min)
a	Exponential	0.6475	49.2
b	Linear	0.6416	41.6
c	Logarithmic	0.7324	65.6
d	Power	0.7189	66.8
	Trend line Average Duration	R Squared	Est. Week 24 (Min)
a	Exponential	0.8731	60.5
b	Linear	0.8597	55.8
c	Logarithmic	0.9815	73.1
d	Power	0.9847	73.7

5.      Analysis

The results of two methods in estimating blog posting week 24 are as follows:

Method	W24 Writing Duration (Min's)	W24 Average Duration (Min's)
Learning Formula	55.52	64.1
Trend Line	65.6	73.1

In trend line method, logarithmic is selected as best equation of writing duration since it has the highest R-squared. Logarithmic is also consistently selected in writing average even though its R-squared is less than Power equation, but it is very slightly difference.

By comparing the duration estimated by learning formula and actual duration as shown in Figure 3, the learning formula is overestimated almost in every blog posting. This is because the learning formula using fixed improvement rate (90%) that means activity is assumed as a full repetitive work. In fact, blog posting is not a full repetitive activity, since the blog topic is always different every week. The activity is the same, blog posting, but the contents of blog is not.

Figure 3. Learning Curve Formula vs Actual

6.      Selection of alternative

As result of that, the trend line method is chosen since it is better in representing the performance of blog posting activity.

7.      Performance monitoring and post-evaluation of results

Learning curve using learning formula is only based on production time 1 and assumed with steady learning/performance rate over time. Meanwhile learning curve using trend line can be based on several data and more representing the actual performance.

To sum up, this shows that applying learning curve using fix formula is suitable for repetitive activity that has same tasks over time. So, it is important to understand the nature of activity when using learning curve concepts.

References:

·         Management Accountant. (2012, Oct 4). Learning Curve Theory. Retrieved from: http://www.managementaccountant.in/2007/04/learning-curve-theory.html

·         NASA. (2012, Oct 4). Learning Curve Calculator. Retrieved from: http://cost.jsc.nasa.gov/learn.html

·         Sullivan, W.G., Wicks, E. M., & Koelling, C. P. (2012). Engineering Economy, pp. 86-89