Estimating the effects of parameter variability on learning curve model predictions

The components of wind power cost are analyzed firstly, which provide an intuitive explanation for understanding the composition of wind power generation. And then a two-factor learning curve model is developed for forecasting future price of wind power. We use the model for practical forecasting and simulating wind power cost from 2012 to 2020, the results obtained demonstrate the credibility and validity of the model.

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The learning curve of laparoscopic holecystectomy in general surgery resident training: old age of the patient may be a risk factor?

Open Medicine ◽

10.1515/med-2016-0086 ◽

2016 ◽

Vol 11 (1) ◽

pp. 489-496 ◽

Cited By ~ 3

Author(s):

Alessia Ferrarese ◽

Valentina Gentile ◽

Marco Bindi ◽

Matteo Rivelli ◽

Jacopo Cumbo ◽

...

Keyword(s):

Laparoscopic Cholecystectomy ◽

Learning Curve ◽

General Surgery ◽

Training Model ◽

Influential Factors ◽

Case Volume ◽

Surgical Trainee ◽

Acceptable Error ◽

Surgical Residents ◽

Curve Model

AbstractA well-designed learning curve is essential for the acquisition of laparoscopic skills: but, are there risk factors that can derail the surgical method? From a review of the current literature on the learning curve in laparoscopic surgery, we identified learning curve components in video laparoscopic cholecystectomy; we suggest a learning curve model that can be applied to assess the progress of general surgical residents as they learn and master the stages of video laparoscopic cholecystectomy regardless of type of patient.Electronic databases were interrogated to better define the terms “surgeon”, “specialized surgeon”, and “specialist surgeon”; we surveyed the literature on surgical residency programs outside Italy to identify learning curve components, influential factors, the importance of tutoring, and the role of reference centers in residency education in surgery. From the definition of acceptable error, self-efficacy, and error classification, we devised a learning curve model that may be applied to training surgical residents in video laparoscopic cholecystectomy.Based on the criteria culled from the literature, the three surgeon categories (general, specialized, and specialist) are distinguished by years of experience, case volume, and error rate; the patients were distinguished for years and characteristics. The training model was constructed as a series of key learning steps in video laparoscopic cholecystectomy. Potential errors were identified and the difficulty of each step was graded using operation-specific characteristics. On completion of each procedure, error checklist scores on procedure-specific performance are tallied to track the learning curve and obtain performance indices of measurement that chart the trainee’s progress.Conclusions. The concept of the learning curve in general surgery is disputed. The use of learning steps may enable the resident surgical trainee to acquire video laparoscopic cholecystectomy skills proportional to the instructor’s ability, the trainee’s own skills, and the safety of the surgical environment. There were no patient characteristics that can derail the methods. With this training scheme, resident trainees may be provided the opportunity to develop their intrinsic capabilities without the loss of basic technical skills.

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Predicting BIM Maturity Based on Learning Curve Model at Firm Level

Construction Research Congress 2018 ◽

10.1061/9780784481264.027 ◽

2018 ◽

Author(s):

Xiaoxiang Xue ◽

Stuart Bernstein ◽

Zhexiong Shang ◽

Hamed Nabizadeh Rafsanjani

Keyword(s):

Learning Curve ◽

Firm Level ◽

Curve Model

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IMPLEMENTATION LEARNING AND FORGETTING CURVE TO PREDICT NEEDS AND DECREASE OF LABORS PERFORMANCE AFTER BREAK

Jurnal Teknologi ◽

10.11113/jt.v77.6909 ◽

2015 ◽

Vol 77 (27) ◽

Cited By ~ 3

Author(s):

Nur Feriyanto ◽

Chairul Saleh ◽

Huda Muhamad Badri ◽

Baba Md Deros ◽

Yudi Pratama

Keyword(s):

Learning Curve ◽

Production Planning ◽

Error Rate ◽

Work Station ◽

Initial Cost ◽

Curve Model ◽

Cost Forecasting ◽

A Company ◽

Additional Labor

A company needs to implement production planning to minimize time and cost. Forecasting and scheduling are two methods which should be conducted in production planning. By implementing the learning and forgetting curve methods, the labor needs as well as the decrease of labors performance after break can be predicted. Firstly, various learning curve models are presented, then each model was analyzed one by one so that the model with the smallest error rate could be determined. A case study conducted in the learning curve model is presented with data derived from the production floor. The four main purposes of this study were to calculate the percentage of each station learning curve, learning and forgetting curves in the company, minimum initial cost, and predict the number of employees needed for the lowest in the number of the work station company. The results in the percentage achieved for the learning curve is 91.47%, the gluing station 78.46%, variation sewing station 98.10%, thumb sewing station 88.17%, omo connect sewing station 89.65%, machine sewing station 87.33%, omo folding sewing station 85.42, rubber tide sewing station 92.51%, sewing station tide studs 72.37%, omo tape sewing station 61.74%, and vilcro sewing station 75.89%, respectively. By analyzing the percentage of each station learning curve, a comparison between the highest and lowest percentage learning curve on the company was made. Thus, it is known that omo tape sewing station needs another operator as the additional labor. The percentage of the forgetting curve is 91.59%. Through a search conducted on the cumulative hours of the productive company, the initial cost of production can be minimized to 15.600 Indonesian rupiah.

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