Methodologies for evaluating sawability of ornamental granite and relation modeling combining sawability with environmental impacts: An application in a stone industrial park of China.

Due to the rapid economic development and urbanization in China, the ornamental stone industry is developing fast, resulting in several environmental problems. Compared with the marble, granite is more difficult to be processed with greater environmental impacts. At present, many advanced and clean technologies are emerging in granite processing field, such as new processing technologies, wastewater treatment system and solid waste reusing technologies. Therefore, a reasonable clean technology planning is crucial for granite processing companies to achieve cleaner production (CP) mode. The purpose of this study is to develop a methodology for evaluating sawability of ornamental granite and constructing the relational model between sawability and environmental impacts from sawing process. The relation model can be used to predict key environmental impacts and support the clean technology planning. This paper firstly develops a characterization mechanism to describe the granite sawability based on Multiple Attribute Decision Making (MADM) theory. The characterization mechanism provides a specialized score system as uniform metric of sawability for ornamental granite. Secondly, definition of sawability function is proposed in this paper to make sawability evaluating process with better operability and applicability. The method for developing the sawability function is investigated combining the characterization mechanism with the design of experiment (DOE) theory. Thirdly, relational models between the granite sawability and the key environmental impacts are investigated by numerical fitting. The uncertainty analysis method for the modeling process is also provided in this paper. The methodology has been applied in a granite processing plant in Laizhou stone industrial park in Shandong province of China. Energy consumption, water consumption and solid waste generation of the plant have been estimated based on the relational models. The models have been proved to be helpful in providing basis for the cleaning technology planning in the plant. [ABSTRACT FROM AUTHOR]