Focus and Scope
The Journal of Smart Lean Manufacturing and Process Enhancement is a forum for researchers and practitioners to share their knowledge and experiences in the field of smart and lean manufacturing. The journal publishes research that addresses the integration of advanced technologies, such as artificial intelligence, the Internet of Things, and big data analytics, with lean manufacturing principles to achieve operational excellence.
Possible Topics
- Smart manufacturing: Industry 4.0, cyber-physical systems, digital twins, artificial intelligence, machine learning
- Lean manufacturing: Value stream mapping, 5S, Six Sigma, lean tools and techniques
- Process improvement: Quality improvement, productivity enhancement, waste reduction
- Supply chain management: Supply chain optimization, sustainability, resilience
- Case studies: Real-world applications of smart and lean manufacturing principles
Potential Keywords:
- Smart manufacturing
- Lean manufacturing
- Process improvement
- Industry 4.0
- Digital transformation
- Operational excellence
- Sustainability
- Supply chain
- Artificial intelligence
- Internet of Things
This journal is dedicated to exploring the intersection of Smart Lean Manufacturing and Process Enhancement , providing a platform for researchers, scholars, and practitioners to share insights on transformative business models, sustainable practices, and innovative strategies that create positive social impact. The journal welcomes high-quality research papers that contribute to the advancement of knowledge in the following areas:
| Main Scope | Description |
|---|---|
| Smart Manufacturing | Covers the application of Industry 4.0 technologies such as IoT, AI, and digital twins in production systems to increase flexibility and efficiency. |
| Lean Manufacturing | Focuses on waste elimination and value maximization through approaches such as 5S, Kanban, Value Stream Mapping (VSM), and Kaizen. |
| Process Improvement | Initiatives to improve processes using statistical or visual methods like Six Sigma, PDCA, DMAIC, and time & motion studies. |
| Supply Chain Management | Strategies for optimizing supply chains based on sustainability, real-time visibility, and logistics resilience. |
| Case Studies | Empirical documentation of smart and lean implementations in real-world industries, including evaluation of outcomes and impacts. |
Here is a detailed table outlining the sub-fields (sub-scopes) within each research area and relevant methodologies that can be applied:
| Main Scope | Sub-Scope | Relevant Methodologies |
|---|---|---|
| Smart Manufacturing | - Cyber-Physical Systems (CPS) - Digital Twin - AI & ML in production | - System Dynamics - Simulation Modeling (e.g., AnyLogic, FlexSim) - Machine Learning (SVM, ANN, etc.) |
| Lean Manufacturing | - Value Stream Mapping (VSM) - 5S Implementation - Kanban, Kaizen | - Action Research - Time and Motion Study - Lean Metrics Analysis |
| Process Improvement | - Six Sigma Projects - Waste Elimination (Muda, Mura, Muri) | - DMAIC, SIPOC - Design of Experiments (DOE) - Statistical Process Control (SPC) |
| Supply Chain Management | - Green Supply Chain - Resilient Network Design - Supply Chain 4.0 | - Multi-Criteria Decision Making (AHP, TOPSIS) - Network Optimization - Simulation & Forecasting Tools |
| Digital Transformation | - ERP-MES Integration - Cloud-Based Manufacturing Monitoring | - Case Study Methodology - Technology Acceptance Models (UTAUT, TAM) |
| Sustainability | - Energy Efficiency - Waste Minimization - Circular Economy Practices | - Life Cycle Assessment (LCA) - Carbon Footprint Analysis - Material Flow Cost Accounting (MFCA) |
| Case Studies | - Industry Implementation Reviews - Pre-and-Post Performance Comparison | - Mixed Methods - Field Observations - KPI Benchmarking |
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