Best Practices in Lean Manufacturing: A Relational Analysis

✍ Scribed by José Roberto Díaz-Reza, Jorge Luis García Alcaraz, Adrián Salvador Morales García

• Publisher: Springer
• Year: 2022
• Tongue: English
• Leaves: 128
• Series: SpringerBriefs in Applied Sciences and Technology
• Category: Library

✦ Synopsis

This book reports four structural equation models (SEM) for quantifying the relationship between the most important lean manufacturing (LM) practices applied to the manufacturing industry. The SEMs are evaluated using 220 responses to a survey applied to manufacturing companies applying LM principles in the production system and are related to: distribution and maintenance, production process and quality system, supply chain and quality, and an integrator model. The findings identify the most important activities for every LM practices and how they are related. These relationship’ values will help administrators, managers, engineers to focus their efforts on these most important activities, facilitating the decision-making process.

✦ Table of Contents

Preface
Contents
List of Figures
List of Tables
1 Lean Manufacturing Origins and Concepts
1.1 What is Lean Manufacturing?
1.1.1 The LM House
1.2 Lean Manufacturing Origins
1.3 Enablers in LM Implementation
1.4 Barriers in LM Implementation
1.5 Lean Manufacturing: Some Applications
1.6 Lean Manufacturing Benefits
1.6.1 Operational Benefits
1.6.2 Social Benefits
1.6.3 Environmental Benefits
1.6.4 Economic Benefits
1.7 Problem Research and Objective
References
2 Some Lean Manufacturing Tools
2.1 General Description of Lean Manufacturing
2.2 Cellular Layouts (CEL)
2.3 Pull System (PUS)
2.4 Small-Lot Production (SLP)
2.5 Quick Setups (SMED)
2.6 Uniform Production Level (UPL)
2.7 Quality Control (QC)
2.8 Total Productive Maintenance (TPM)
2.9 Supplier Networks (SUN)
2.10 Flexible Resources (FLR)
2.11 Inventory Minimization (INMI)
References
3 Methodology
3.1 Introduction
3.2 Literature Review
3.3 Proposed Questionnaire
3.4 Final and Validated Questionnaire
3.5 Questionnaire Application to Industry
3.6 Data Capture and Debugging
3.7 Statistical Data Validation
3.8 Descriptive Analysis of Items
3.9 Structural Equation Model
3.9.1 Direct Effects
3.9.2 Sum of Indirect Effects and Total Effects
3.10 Sensitivity Analysis
3.11 Statistical Model Interpretation
References
4 Model 1. Distribution and Maintenance
4.1 Model Variables and Validation
4.2 Descriptive Analysis
4.3 Hypotheses in the Model
4.4 Evaluation of the Structural Equation Model
4.4.1 Direct Effect and Effect Size
4.4.2 Sum of Indirect Effects
4.4.3 Total Effects
4.4.4 Sensitivity Analysis
4.5 Conclusions and Industrial Implications
4.5.1 From the Structural Equation Model
4.5.2 Conclusions of the Sensitivity Analysis
Annex: Additional Data for Support Validation
References
5 Model 2. Pull System and Quality Control
5.1 Model Variables and Their Validation
5.2 Descriptive Analysis of Items
5.3 Hypotheses in the Model
5.4 Structural Equation Model Evaluation
5.4.1 Direct Effects and Effect Sizes
5.4.2 Sum of Indirect Effects
5.4.3 Total Effects
5.4.4 Sensitivity Analysis
5.5 Conclusions and Industrial Implications
5.5.1 Conclusions from the Structural Equation Model
5.5.2 Conclusions from the Sensitivity Analysis
Annex: Additional Data for Support Validation
References
6 Model 3. Supplier Network and Inventory Minimization
6.1 Model Variables and Their Validation
6.2 Descriptive Analysis of the Items
6.3 Hypotheses in the Model
6.4 Evaluation of the Structural Equation Model
6.4.1 Direct Effects and Effect Sizes
6.4.2 Sum of Indirect Effects
6.4.3 Total Effects
6.4.4 Sensitivity Analysis
6.5 Conclusions and Industrial Implications
6.5.1 Conclusions of the Model
6.5.2 Conclusions of the Sensitivity Analysis
Annex: Additional Data for Support Validation
References
7 Model 4. Integrative Model
7.1 Model Variables and Their Validation
7.2 Hypotheses in the Model
7.3 Structural Equation Model Evaluation
7.3.1 Direct Effects and Effect Size
7.3.2 Sum of Indirect Effects
7.3.3 Total Effects
7.3.4 Sensitivity Analysis
7.4 Conclusions and Industrial Implications
7.4.1 Conclusions from the Structural Equation Model
7.4.2 Conclusions from the Sensitivity Analysis
Annex: Additional Data for Support Validation
References