Welcome! Click to reach the link!


Home
  
About Me
 
In China
 In Germany
 In USA
 My Resume
  
Publications
 Books
 Technical Papers
 Theses
 Others
 
Info Tech
 A Move To IT
 
Courses Attended
 Certificates
 Software Projects
 
FEM Simulation
 
Engineering
 Work and Study
 Courses Attended
 Process Modeling
 
Photo Album
 
China
 Germany
 
PhD Defense/Celeb.
 
Miner Parade
 USA
 Scenic & Architecture
 
Hobbies
 
Resources Links


 

| Home | About Me | Publications | Info Tech | Engineering | Hobbies | Resource Links |

[Resume] [Books] [Technical Papers] [Software Projects] [FEM Simulation] [Process Modeling]     

 



High Quality & Low Cost Strategies
(General Strategy)
 

 

Strategy Summary

(1) Modeling + ML (for high-accurate Models)
Online data is used to build online model. After many stages of Machine Learning, the model is very accurate! For example, to use data before last year's January to build model.  Since in the last Year's January the measured data is available, so a Machine Learning is carried out. Then used the model after this ML to do the ML for the last Year's February, and then to do the ML for last years March, April, ... until this years March. After so many ML the model is very accurate!

(2) Integration of Basic Automation, Model-based System, MES and ERP
This is to integration Basic Automation (the Level 1 System), Model-based System (the Level 2 System), MES (the Level 3 System) and ERP (the Level 4 System). Since any system can be sold for multiple times, the price is lower. Some system is with very high quality, such as ERP system SAP. Therefore, the cost-quality relation is good.

(3) Customer returns usually over 1000%!
(for every dollar I earned, the client makes over 10 dollars or more)! In one consulting work I increased 70% utilization for $1 billion investment (company N1)! One highest ratio even reached $700 Million (in NISCO case)!



Detailed Strategies

(a) Strategy 1: Modeling & Model Accuracy via Machine Learning

 (1) Modeling based on my Ph.D. on Engineering

 (2) Machine Learning (ML) with online data to increase model Accuracy (so usual errors below 1%)
   * for the industry I am familiar with: Direct modeling based on my Engineering Ph.D.
   * for the industry I am not familiar with: Deep Learning (to establish relations between goals and influence factors)

(b) Strategy 2: Integration (Multi-Levels)

 - Level1 System: Basic Automation/Control

 - Level 2 System: Model-based, representing engineering logics for example

 - Level 3 Systems: MES (Manufacturing Executing System)

 - Level 4 Systems: ERP (e.g. SAP)

(c) Software Architecture

With excellent models and data, and based on project goal (with it the model was designed), software are developed and thus, problems are solved (rich experiences achieved in architecture over 200 projects).

Note: Use Cloud Computing to collect remote data, as in in companies B1, S1, T1, B2, etc.
 

***Architected Projects

(i) General IT Projects Architecture Details: Projects Architecture Details in general IT Software Development I have completed, dozens of pages to even over a 1000 pages for each design ...

(ii) Engineering Projects Architecture Details: Projects Architecture Details on Engineering Software Development I have completed, dozens of pages to even over a 1000 pages for each design ...
 

 

 


  You are welcome to contact me. Send e-mail to me or give me a call.

 
Bingji (Benjamin) Li 2009. All rights reserved.