The Development of a Power/Energy Consumption Model For Multiprocess Machining Operations
 
 

Douglas G. Mattes | UIUC | MS | 1990

ABSTRACT:

Throughout the American industrial sector, production and manufacturing costs have steadily increased in the past several decades. These cost increases stem from many areas of production, such as labor costs, material costs, machine repair costs, and overhead costs. Corporations and agencies have thus had to take actions to reduce these increases. But at the same time, they have also had to try to keep production levels high and assure that only quality parts are produced. For manufacturing facilities, the simultaneous satisfaction of these requirements has been very difficult, especially if the manufacturing processes are not well understood. Therefore, a key to reducing manufacturing costs while at the same time keeping production levels and quality levels high is to develop models that will provide a better understanding of the basic manufacturing processes, such as turning, boring, and milling.
 

One approach to obtaining lower manufacturing costs is through the use of manufacturing process models which will aid in the determination and reduction of the amount of energy consumed that is directly attributable to manufacturing processes. In the past, many organizations have successfully used multiple regression models to characterize total energy consumption patterns. These models, however, are not capable of determining what portion of the total energy consumed is directly attributable to manufacturing processes, as opposed to energy consumed as overhead for heating, cooling, lighting, etc. The use of regression models requires that data be collected before the model can be developed. This limits the usefulness of the existing models -for they are only valid for the machining parameters that the tests were run under. Knowledge of process energy consumption and the parameters that influence it would allow for an assessment of the potential reduction in the energy used in manufacturing.
 

The overall objective of this research is to develop a mechanistic model based on machining parameters that can be used to predict cutting forces and machining energy prior to any actual cutting. Such a model would be more general than the regression models currently being used. The model to be developed will be a multiprocess model capable of predicting cutting forces and process energy for a series of machining operations including turning, boring, and face milling. This overall objective will be met by completing the following tasks:

1) The force and power prediction models for each of the three machining processes will be developed independently.
2) Each model will be calibrated using the experimental test data.
3) Further experimentation will then be needed to verify the accuracy of the model predictions over a range of machining conditions, as well as for a variety of workpiece and cutter materials.
4) Finally, when all models are complete, they will be integrated to form one composite multiprocess model.

Although the multiprocess composite model will consist of all three processes mentioned above, no experimentation was performed for the boring operation. The force and power models for boring have been developed; however, they are not calibrated or verified. Therefore, in the above tasks, steps 2 & 3 apply only to the turning and face milling operations.
 

The integrated model, resulting from task 4, will be formulated into a machining process computer simulation program, called METSIM, on an IBM Personal Computer. The new model could then be used as a design tool to optimize machining parameters for any of the three processes mentioned above, since the cutting forces and process energy can be predicted before the actual machining. This thesis will describe recent work performed at the University of Illinois for the development of manufacturing process models which can be used to determine the forces generated and the amount of energy consumed during machining operations.

The Manufacturing Research Group in the Mechanical and Industrial Engineering Department at the University of Illinois has recently been performing research which has led to the development of mechanistic force models for the turning, boring, and milling operations. These models are used to determine the forces that are produced in a certain machining operation given the cutting conditions, process plans, tool and cutter geometries, and workpiece and cutter materials as inputs. This research furthers the development of the existing force models and uses them as a basis for developing power consumption prediction models. The resulting power prediction models use as inputs the force components that were determined for certain workpiece materials, cutter geometries, and cutting conditions. The output of the power prediction models is the energy consumption values and the power requirements for the given set of machining conditions. Three power consumption models, for the processes given above, turning, boring, and face milling, will be addressed. These power consumption models are not only effective tools for machining power cost control, they are also useful for evaluating power requirements for certain cutting operations, which allow engineers and operators to determine if a certain cutting process will surpass the maximum power rating for a machine.

The remainder of this thesis is organized into seven chapters and an appendix which contains information on the calibration of the force dynomometer used for model development. A review of previous work performed in the creation of cutting force models and power/energy models for several manufacturing processes is given in Chapter 2. Chapter 3 continues with a description of the cutting force models and the development of the power/energy models which are used in a machining process computer simulation program, called METSIM, for the turning, boring, and face milling processes. The experimental environment for the calibration tests and the verification tests for the turning and face milling models is presented in Chapter 4. No experimentation was performed for the boring operation. Chapter 5 will discuss the calibration process used for the determination of the two cutting constants KN and KF for the turning and face milling operations. The results of verification tests conducted for the turning and face milling models will be discussed and analyzed in Chapter 6. Chapter 7 will use the turning simulator as an example to observe the effects of the variation of five different process parameters on the power requirement values. This chapter will also demonstrate the use of the power/energy models in selecting optimum machining process plans. Finally, presented in Chapter 8 will be a discussion of the results of this research and suggestions for further work.

If you have any comments or suggestions please e-mail jwsuther@mtu.edu.