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Using Lean Practices to Improve Current Carbon Labelling Schemes for Construction Materials— a General Framework

Author(s):

Medium: journal article
Language(s): English
Published in: Journal of Green Building, , n. 1, v. 7
Page(s): 173-191
DOI: 10.3992/jgb.7.1.173
Abstract:

The construction industry has considerable environmental impacts through the process of manufacturing building materials and building construction. Many environmental labelling programs have been introduced to the construction industry to measure the environmental impacts, including building up the environmental profiles for building materials. Although absolute measurements of the environmental impacts can be obtained by these labelling programs through detailed Life Cycle Assessment (LCA) studies, relative measurements should not be overlooked to indicate the gap between the current and the “leanest” performance. The term “lean” is often used to describe a process with less wastes, materials, human effort, time, etc. The lean concept originates from the Toyota Production System and has been applied in the automobile industry for decades. This paper therefore aims to investigate the applicability of a relative measurement of the environmental impacts for building materials by introducing the concept of “lean score”. The research aim is narrowed down by choosing the carbon labelling program and the precast concrete products as research objectives. The results indicate that a “lean” benchmark can be built to offer relative measurements of carbon emissions for precast concrete products. The lean score obtained from the benchmarking process provides the improving potential that can help the construction industry move towards sustainability. The results are also useful for regulatory bodies to establish national standards to measure the environmental impacts for building materials.

Structurae cannot make the full text of this publication available at this time. The full text can be accessed through the publisher via the DOI: 10.3992/jgb.7.1.173.
  • About this
    data sheet
  • Reference-ID
    10517048
  • Published on:
    11/12/2020
  • Last updated on:
    19/02/2021