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The Importance of Data Quality in Using LCA Approach as A Decision Supporting Tool: Comprative Case Study between Injection Moulding Machines in Processing Polypropylene
Author(s) -
Sharah Yunihar Saputra,
Jessica Hanafi
Publication year - 2017
Publication title -
indonesian journal of life cycle assessment and sustainability
Language(s) - English
Resource type - Journals
ISSN - 2548-804X
DOI - 10.52394/ijolcas.v1i2.30
Subject(s) - life cycle assessment , reuse , quality (philosophy) , product (mathematics) , production (economics) , computer science , environmental impact assessment , engineering , manufacturing engineering , waste management , mathematics , philosophy , geometry , epistemology , economics , macroeconomics , ecology , biology
Indonesia is developing an awareness of life cycle perspective, where a product cannot only be analysed in a certain phase but shall be analysed throughout its life cycle. In developing this concept, the understanding of data quality in selecting and recording datasets is important. Many LCA practitioners often neglected the importance of understanding different types of datasets and tracking and documenting dataset. The objective of this paper is to understand the effect of technology coverage in data quality of Life cycle assessment (LCA) and the use of LCA approach as a decision supporting tool. A case study comparing two production methods of a product made of polypropylene (PP) is conducted. Injection moulding machines used in these two plants are different in terms of technology aspect. Comparison between injection moulding machines in these plants was conducted and actual data from the production site were gathered. SimaPro 8 by Pre Consultants is used for life cycle assessment of the machines. Two types of methods, i.e. TRACI and ReCipe, are used in impact assessment stage. The result implied that the technology difference shows significant variation of impact related to energy consumption between both plants. Therefore careful consideration must be taken when using and recording datasets to ensure suitability of the datasets for reuse.

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