Knowledge Labor Measurement - Theory and Application

Author: Shi Liangping
Publisher:
Publish Date: 2007-01-01
Features: This book creatively applies advanced tools from the field of industrial engineering to the measurement of knowledge labor, providing an effective solution to real-world management challenges. The main purpose of this book is to analyze knowledge labor, the process of knowledge labor, and the characteristics of the knowledge labor process, while tentatively exploring the measurement of knowledge labor. The book consists of eight chapters. The preface outlines knowledge and knowledge labor, proposes the research content and framework of the book, and provides an overview of the chapter structure.
1. Overview of Labor Measurement Theory: This chapter explains the concept of labor measurement, the scales 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 elaborates on the fundamental theories of fuzzy set theory, including basic concepts, operations of 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 basic 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, models, and applications of artificial neural networks.
3. Theoretical Analysis of Knowledge Labor Measurement: This chapter discusses knowledge labor and its fundamental 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 knowledge labor process 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 knowledge quantity of the engineering design process, the decomposition and expansion of the engineering design process, and the knowledge quantity of the engineering design process, establishing a process-oriented, knowledge-quantity-based engineering design labor measurement model. It also investigates the fuzzy knowledge representation structure model of engineering design objects and 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 Models: 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 design philosophy of the measurement system and its composition and structure, studying the structural framework and data flow diagrams of the sample acquisition subsystem, measurement model subsystem, model database subsystem, and measurement subsystem.
8. Conclusion: This chapter compares the characteristics of the two knowledge labor measurement theories and methods and provides an outlook for further research.