Data clustering and fuzzy neural network for sales forecasting: A case study in printed circuit board industry

2009 ◽  
Vol 22 (5) ◽  
pp. 344-355 ◽  
Author(s):  
Pei-Chann Chang ◽  
Chen-Hao Liu ◽  
Chin-Yuan Fan
Keyword(s):  
Neural Network ◽  
Data Clustering ◽  
Fuzzy Neural Network ◽  
Printed Circuit Board ◽  
Circuit Board ◽  
Printed Circuit ◽  
Fuzzy Neural ◽  
Board Industry

A Novel Forecasting Model Based on Support Vector Regression and Bat Meta-Heuristic (Bat–SVR): Case Study in Printed Circuit Board Industry

2015 ◽  
Vol 14 (01) ◽  
pp. 195-215 ◽  
Author(s):  
Amirmohammad Tavakkoli ◽  
Jalal Rezaeenour ◽  
Esmaeil Hadavandi
Keyword(s):  
Support Vector Regression ◽  
Printed Circuit Board ◽  
Bat Algorithm ◽  
Circuit Board ◽  
Support Vector ◽  
Forecasting Model ◽  
Printed Circuit ◽  
Proposed Model ◽  
Board Industry

Sales forecasting is very beneficial to most businesses. A successful business needs accurate sales forecasting to understand the market and sales trends. This paper presents a novel sales forecasting model by integrating support vector regression (SVR) and bat algorithm (BA). Since the accuracy of SVR forecasting mainly depends on SVR parameters, we use BA for tuning these parameters because Bat is a newly introduced algorithm and has many parameters. In order to find the best set of BA parameters Taguchi method was utilized. We validated our model on four known UCI datasets. Then we applied our model in printed circuit board (PCB) sales forecasting case study. We compared the accuracy of the proposed model with Genetic algorithm (GA)–SVR, particle swarm optimization (PSO)–SVR, and classic-SVR. The experimental results show that the proposed model outperforms the others. To ensure the robustness of our proposed model, sensitivity analysis was also done using our model to find out the effects of dependent variables values on sales time series.

scholarly journals Estimation of the PCB Production Process Using a Neural Network

2020 ◽  
Vol 15 ◽  
pp. 01-07
Author(s):  
Kuo-Hsien Hsia ◽  
Jr-Hung Guo
Keyword(s):  
Neural Network ◽  
Production Process ◽  
Manufacturing Process ◽  
Printed Circuit Boards ◽  
Printed Circuit Board ◽  
Circuit Board ◽  
Circuit Boards ◽  
Electronic Products ◽  
Printed Circuit ◽  
Board Industry

Printed Circuit Boards (PCB) are an integral part of all electronic products, and the production process for printed circuit boards is quite complex. As the life cycle of electronic products becomes shorter and shorter, and the precision and signal bandwidth of electronic products become higher and higher, the manufacturing process of printed circuit boards is further complicated. Therefore, how to pre-evaluate the production difficulty before starting the production will effectively increase the efficiency and quality of printed circuit board production. Gerber file is the most commonly used data format for the printed circuit board industry. This file contains most of the parameters required for the manufacture of printed circuit boards. Therefore, this study uses a neural network to evaluate new PCB products before they are produced through the production parameters that are more influential in the PCB manufacturing process. This makes it possible to evaluate the difficulty and the required production process before the new PCB product is produced. This will be very beneficial for the PCB production schedule, quality control, and cost.

Application of Lock-in Thermography on PCB for Fault Localization and Validation of Failure Mechanism Due to External Discrete Component Variation

2010 ◽  
Author(s):  
William Ng ◽  
Kevin Weaver ◽  
Zachary Gemmill ◽  
Herve Deslandes ◽  
Rudolf Schlangen
Keyword(s):  
Failure Mechanism ◽  
Integrated Circuit ◽  
Printed Circuit Board ◽  
Hot Spot ◽  
Circuit Board ◽  
Discrete Component ◽  
Printed Circuit ◽  
Thermal Signature ◽  
Lock In

Abstract This paper demonstrates the use of a real time lock-in thermography (LIT) system to non-destructively characterize thermal events prior to the failing of an integrated circuit (IC) device. A case study using a packaged IC mounted on printed circuit board (PCB) is presented. The result validated the failing model by observing the thermal signature on the package. Subsequent analysis from the backside of the IC identified a hot spot in internal circuitry sensitive to varying value of external discrete component (inductor) on PCB.

Temperature and Humidity Dependent Reliability Analysis of RGB LED Chips

2006 ◽  
Author(s):  
Jun-Xian Fu ◽  
Shukri Souri ◽  
James S. Harris
Keyword(s):  
Reliability Analysis ◽  
Printed Circuit Board ◽  
Light Emitting Diode ◽  
Circuit Board ◽  
Light Emitting ◽  
Printed Circuit ◽  
Root Cause ◽  
Micro Cracks ◽  
Temperature And Humidity

Abstract Temperature and humidity dependent reliability analysis was performed based on a case study involving an indicator printed-circuit board with surface-mounted multiple-die red, green and blue light-emitting diode chips. Reported intermittent failures were investigated and the root cause was attributed to a non-optimized reflow process that resulted in micro-cracks and delaminations within the molding resin of the chips.

scholarly journals Decarbonization of Industrial Energy Systems: A Case Study of Printed Circuit Board manufacturing

2021 ◽  
Author(s):  
Carles Ribas Tugores ◽  
Gerald Birngruber ◽  
Jürgen Fluch ◽  
Angelika Swatek ◽  
Gerald Schweiger
Keyword(s):  
Printed Circuit Board ◽  
Energy Systems ◽  
Circuit Board ◽  
Printed Circuit ◽  
Printed Circuit Board Manufacturing ◽  
Industrial Energy
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