Knowledge Labor Measurement: Theory and Application

Author: Liu Gang
Publisher:
Publish Date: 2007-01-01
Features: This book consists of eight chapters. The preface outlines knowledge and knowledge labor, proposes the content and framework of the research in this book, and provides the chapter arrangement.
1. Overview of Labor Measurement Theory
This chapter elaborates on the concept of labor measurement, the scale of labor measurement, the principles of labor measurement, the significance of labor measurement, and the basic methods of labor measurement.
2. Theoretical Basis of Knowledge Labor Measurement
This chapter discusses the fundamental theories of fuzzy set theory, including basic concepts of fuzzy sets, operations on fuzzy sets, membership functions of fuzzy sets, fuzzy logic and reasoning, and fuzzy comprehensive evaluation. It also provides an overview of the basic content of knowledge engineering, primarily stating the fundamental methods of knowledge representation, such as predicate logic, production rules, semantic web, characteristic tables, direct or simulated knowledge representation, and fuzzy knowledge representation. Additionally, it analyzes artificial neural network models, learning rules of artificial neural networks, artificial neural network models, and applications of artificial neural networks.
3. Analysis of Knowledge Labor Measurement Theory
This chapter examines knowledge labor and its basic characteristics, the similarities and differences between knowledge labor and mental labor, the current status and challenges of knowledge labor measurement. Based on this, it studies the process of knowledge labor and its three essential characteristics, proposing the basic ideas of process-oriented, knowledge-quantity-based knowledge labor measurement and object-oriented, knowledge-processing-based knowledge labor measurement.
4. Methods of Knowledge Labor Measurement
Based on the theory of knowledge labor measurement, this chapter introduces the principles of tree diagrams, fuzzy set theory, and neural network methods to establish a process-oriented, knowledge-quantity-based labor measurement method. It also applies fuzzy logic knowledge representation techniques and neural network knowledge processing methods to establish an object-oriented, knowledge-processing-based labor measurement method.
5. Application of Knowledge Labor Measurement Theory and Methods—Engineering Design Labor Measurement Model
This chapter studies the decomposition and expansion of the engineering design process and the knowledge quantity of the engineering design process based on the knowledge quantity of the engineering design process. It establishes a process-oriented, knowledge-quantity-based engineering design labor measurement model and researches the fuzzy knowledge representation structure model of engineering design objects. It also applies neural network knowledge processing methods to establish an object-oriented, knowledge-processing-based engineering design labor measurement model.
6. Application Examples of Engineering Design Labor Measurement Model
Taking the shrimp grading machine and chair design as examples, this chapter provides an analysis of the application of both the process-oriented, knowledge-quantity-based engineering design labor measurement model and the object-oriented, knowledge-processing-based engineering design labor measurement model.
7. Knowledge Labor Measurement System
This chapter presents the ideas of measurement system design, the composition and structure of the measurement system, and studies the structural framework and data flow diagrams of the sample acquisition subsystem, measurement model subsystem, model database subsystem, and measurement subsystem in the system.
8. Conclusion
This chapter provides a comparative analysis of the characteristics of the two knowledge labor measurement theories and methods and offers prospects for further research.