Systems/line level – The second example is drawn from the research of Dr. Stefanie Robinson (S. Robinson, “An Environmental and Economic Trade-Off Analysis of Manufacturing Process Chains to Inform Decision Making for Sustainability,” Ph.D. Thesis, University of California, Mechanical Engineering, 2013) and focuses on the energy and resource consumption in a process chain with the objective of establishing a basis for trading off the potential for upgrading specific operations in the line. This was based on research conducted with a major heavy equipment manufacturer in the US. The figure below shows a schematic of a multiple operation process chain and a detail of one of the process operations with typical input and output of energy and other consumables along with waste and emissions.
With a representation of a process chain, and the individual operations, one then needs to determine the consumption and rate of outflow of the major consumables and waste streams. One can appreciate that it is necessary to do a rather detailed analysis of the inputs and outputs (wasted and worn tooling, scrap from production, leakages, etc.) to be accurate. With this data, the actual resource consumption and associated economic and environmental cost can be determined. Then, the impact of changes in any of the production steps can be evaluated both in terms of productivity and quality as well as environmental (energy, global warming, water) effects and associated costs as shown below.
System consumption metrics and environmental and economic “cost”
Process level – This third and last example bores in more finely on the process level detail for a machining operation. Data from this level of analysis would feed into the systems/line level just described. This example also draws on the work of Dr. Nancy Diaz in the above cited thesis. This work developed a generic method for calculating energy consumption during a realistic machining operation on a precision milling machine based on constant and variable contributions of the material removal rate (MRR). The MRR is a driver of productivity in a machining operation and is based on real time data of the feed rate of the cutting tool, the cutting speed and the depth or width of engagement in the case of milling studied here. This data is now available in real time from the machine controller thanks to standardized interfaces and data formats such as MTConnect and associated software. It is also available from the numerical control program driving the machining operation (that is the path the cutting tool takes in the machining operation) but that is often inaccurate due to actual the performance of the machine in operation. The curve below shows the specific energy (Joules/cubic millimeter, J/mm3) as a function of MRR.
The significance of this data is that the designer or production engineer can determine the energy to create a part feature from knowledge (either estimated from the tool path or measured in process). And, this was determined for a variety of machining conditions with different tooling – so it has some breadth of application. For other materials, however, the curve would likely shift up (if a more challenging material to machine – more energy per unit of material removed) or down (if easier to machine).
