Hybrid FMEA-DEMATEL-MADM model prioritizes waste reduction in steel plate manufacturing

Category: Resource Management · Effect: Strong effect · Year: 2023

A hybrid analytical model combining FMEA, DEMATEL, and PCIM-MADM can systematically identify and prioritize waste-producing factors in steel plate manufacturing, leading to more effective resource management and sustainable production.

Design Takeaway

Integrate a multi-faceted risk assessment framework, such as the hybrid FMEA-DEMATEL-MADM model, into the design and production planning stages to systematically identify and mitigate waste.

Why It Matters

This research offers a structured, data-driven approach for designers and engineers to tackle waste in complex manufacturing processes. By pinpointing critical waste factors and their interdependencies, it enables targeted interventions that enhance material efficiency and reduce environmental impact, aligning with global sustainability goals.

Key Finding

A combined approach using FMEA, DEMATEL, and MADM methods successfully pinpointed the most significant sources of waste in steel plate production and ranked them for targeted improvement efforts.

Key Findings

Research Evidence

Aim: To develop and validate a hybrid evaluation model for identifying and prioritizing waste-producing factors in steel plate manufacturing to support sustainable development.

Method: Hybrid Analytical Model (FMEA, DEMATEL, PCIM-MADM)

Procedure: The study involved on-site inspections to identify waste sources, followed by DEMATEL to analyze the interrelationships between risk factors, and PCIM-MADM to aggregate and evaluate risk scores for prioritization of corrective actions.

Context: Steel plate manufacturing industry

Design Principle

Systematic waste identification and prioritization are crucial for achieving resource efficiency and sustainable manufacturing.

How to Apply

When designing or redesigning a manufacturing process, conduct a thorough risk assessment using FMEA to identify potential failure modes leading to waste. Then, use DEMATEL to map the causal relationships between these failure modes and employ a multi-attribute decision-making technique like MADM to quantify and rank the severity of waste generation for targeted interventions.

Limitations

The model's effectiveness may depend on the accuracy of initial data collection and expert input. Generalizability to other manufacturing sectors requires further validation.

Student Guide (IB Design Technology)

Simple Explanation: This study shows how to use a smart checklist (FMEA) combined with a network map (DEMATEL) and a scoring system (MADM) to find the biggest ways a factory making steel plates is wasting materials and energy, so they can fix those problems first.

Why This Matters: Understanding and reducing waste is a key part of designing responsibly and sustainably. This research provides a method to systematically find and fix waste in a real-world manufacturing setting.

Critical Thinking: How might the interdependencies identified by DEMATEL influence the prioritization of corrective actions, and what are the potential trade-offs when addressing highly interconnected waste factors?

IA-Ready Paragraph: This research highlights the importance of systematic risk assessment in sustainable production. The hybrid FMEA-DEMATEL-MADM model provides a robust framework for identifying and prioritizing waste factors in manufacturing processes, offering valuable insights for optimizing resource efficiency and minimizing environmental impact.

Project Tips

How to Use in IA

Examiner Tips

Independent Variable: ["Waste-producing factors in steel plate manufacturing","Interconnectedness of risk factors"]

Dependent Variable: ["Prioritization of corrective actions for waste reduction","Risk scores of waste factors"]

Controlled Variables: ["Specific steel plate manufacturing process","Factory conditions","Expert judgment criteria"]

Strengths

Critical Questions

Extended Essay Application

Source

Risk Assessment in Sustainable Production: Utilizing a Hybrid Evaluation Model to Identify the Waste Factors in Steel Plate Manufacturing · Sustainability · 2023 · 10.3390/su152416583