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A STUDY ON CALCULATION METHODS OF ENVIRONMENTAL
BURDEN FOR NC PROGRAM DIAGNOSIS
1
1
2
H. Narita , T. Norihisa , L. Y. Chen , H. Fujimoto 1 and T. Hasebe 2
'Graduate School of Engineering, Nagoya Institute of Technology,
Gokiso-cho, Showa-ku, Nagoya, Aichi, 466-8555, Japan
2
OKUMA Corporation,
5-25-1, Shimokoguchi, Oguchi-cho, Niwa-gun, Aichi, 480-0193, Japan

ABSTRACT

Some activities for environmental protection have been tried to reduce environmental burdens in a lot
of fields. Manufacturing field is also required to reduce them. Hence, prediction system of
environmental burden for machining operation is proposed based on LCA (Life Cycle Assessment)
policy. This system can calculate environmental burden (equivalent CO2 emission) due to the electric
consumption of a machine tool, the cutting tools status, the coolant quantity, the lubricant oil quantity
and the metal chips, and provide the information of the accurate environmental burden of the
machining process by considering some activities related to the machine tool operations. In this paper,
the development status of prediction system is described. As a case study, two NC programs that
manufacture simple shape are also evaluated to show the feasibility of it.

KEYWORDS
Environmental burden, Life Cycle Assessment, Production cost, Machine tool operation, Virtual
machining, NC program diagnosis

INTRODUCTION
Manufacturing technologies pursuing the sustainable development are required due to the evident
environmental impacts like global warming, ozone layer depletion and acidification, so manufacturing
system has to be reassessed from the view point of environmental protection. Hence an accurate
evaluation system of environmental impacts for manufacturing is required. But it is difficult to
evaluate environmental impacts because we can not recognize them. In this research, a prediction
system of the environmental burden for a machining operation is proposed based on LCA (Life Cycle
Assessment) (SETAC, 1993) policy for future manufacturing system. This kind of system will enable
engineers to decide the machining strategies, to generate the production scheduling and to evaluate the