COMPUTING FOR GREEN MACHINING

Recent Results and Research Perspectives

Paul Xirouchakis and Oliver Avram

Institute of Mechanical Engineering, Swiss Federal Institute of Technology in Lausanne, Ecublens, Switzerland

Keywords: Green machining, Holistic process planning optimization, Green controller.

Abstract: We present our vision of research for the development of green machine tools focused on information

technology issues. We present first what are the characteristics of a green machine tool, its life cycle aspects

and the related environmental considerations. We proceed afterwards with needed research in the area of

modeling, optimization and associated planning, controlling and scheduling software tools at the process,

process planning, machine tool life cycle, factory and manufacturing network level. Finally we present some

of our recent advances related to energy consumption modeling in milling.

1 INTRODUCTION

Our objective in this paper is to present a research

agenda for green machine tools focused on

information technology issues. Some work has been

reported in the literature (Munoz, Sheng, 1995,

Dornkudwar, et al, 1998, Srinivasan, Sheng, 1999a-

b, Akbari, et al, 2001, Dahmus, Gutowski, 2004,

Jayal, Balaji, 2007, Narita et al, 2006, Zhigang et al

2008 etc.) considering green machining issues;

however, in most cases the focus has been limited at

the process and process planning level. We wish to

present a broader perspective that also includes

system level considerations (several machine tools

or distributed manufacturing) as well total life cycle

coverage. In the last section we present some of our

recent work related to this research agenda.

Basically, in the normal course of machining

several environmental discharges occur in solid,

liquid or gaseous state as a result of the interaction

between the tool, workpiece and the cutting fluid,

whereas the machine tool system accommodating

the process draws a specific amount of power related

to machining and non-machining activities.

Generally, research studies are focused on the

cutting energy in machining systems, that is, the

amount of energy required to remove a specific

amount of material. However, from the point of

view of green manufacturing the energy

consumption should be considered systematically for

the whole machine tool system and not limited

solely to the cutting energy which represents just a

variable amount highly dependent on process

parameters.

2 BACKGROUND

2.1 What is a Machine Tool System?

We will focus our presentation on green machining.

We consider all systems (see Figure 1) that are

participating in the delivery of the machining

function, i.e. not only the main machining system

with its spindle and feed axes subsystems but also

Figure 1: A Machine Tool System (MTS).

Xirouchakis P. and Avram O. (2010).

COMPUTING FOR GREEN MACHINING - Recent Results and Research Perspectives.

In Proceedings of the Multi-Conference on Innovative Developments in ICT, pages 25-31

DOI: 10.5220/0002960600250031

 SciTePress

Figure 2: The life cycle of a Machine Tool System (MTS).

the auxiliary systems such as the cutting fluid, chip

removal and tool management systems. This is

important since the energy consumption and

associated environmental impacts are also strongly

dependent on the auxiliary systems.

2.2 What is the Life-Cycle of a

Machine Tool System?

Before attempting to define what are the green

aspects of a machine tool system it is important to

consider the entire life cycle of a machine tool

system from its design phase to its manufacturing,

use and end-of-life (see Figure 2). In each life cycle

phase we need to consider the energy and raw

materials consumption and the corresponding

generated waste and emissions.

However, it is important to mention that the use

phase seems to be one of the most important life

cycle phases of the machine tool system, where most

of the energy consumption and environmental

impact is taking place.

Figure 3: Life cycle crossing of a Machine Tool System.

In that regard it is also important to note that the

life cycle of the machine tool is crossing the life

cycle of the part that is manufactured i.e. when a

part is machined (the machining life cycle phase for

the part) a machine tool is used (the use life cycle

phase for the machine tool system). This is the well

known life cycle crossing problem (Young et al,

1997) of machining, already reported in the

literature (see Figure 3). Life cycle crossing implied

that we cannot consider the life cycles of the

machine tool system and that of the part separately

since they are interdependent. For example, a

machine tool system that machines a part with a

higher quality is greener (if all other aspects are the

same) since the life cycle of the part is extended.

2.3 What are the Environmental

Considerations?

The environmental objectives for a machine tool

system are mainly, as we remarked above, related to

its use phase in order to reduce its energy

consumption, to reduce (or even better to completely

eliminate) the disposal of hazardous substances

(such as the disposed cutting fluid), to improve the

surrounding air quality (so as to eliminate the

corresponding health impacts) and to reduce

resource consumption (in addition to energy, such as

cutting fluid and other consumables such as cutting

fluid filters and tools).

2.4 What is a Green Machine Tool

System?

Based on the previous discussions we can mention

some desired aspects to achieve the goal of a green

machine tool system. A green machine tool system

should have reduced installed power for its various

motorized equipment in order to reduce the energy

consumption. This is especially true since in many

cases a far lower power is used to achieve the

needed machine task than the installed power

capacity. Another aspect of a green machine tool

system is the reduction or complete elimination of

the hazardous waste and emissions. For example dry

machining could be promoted to eliminate the need

for using a cutting fluid but this may entail the

deterioration of the air quality and the reduction of

INNOV 2010 - International Multi-Conference on Innovative Developments in ICT

the life duration of the tool.

3 RESEARCH VISION FOR

GREEN MANUFACTURING

3.1 Modeling, Optimization and

Software Tools

Our focus is to describe needed research on

modeling, optimization and corresponding software

tools. In this regard we propose a hierarchy of

research issues as illustrated in Figure 4. We propose

a hierarchy of research issues in order to facilitate

the modeling of a complex manufacturing system by

decomposing the system in its components. Each

level of the decomposed hierarchy corresponds to a

separate physical component which can be modeled

stepwise. We will now describe the modeling of

each level of the hierarchy.

At the very basic level we need process modeling

and optimization methods and tools. For example we

need to develop eco-evaluation models for the

following alternative processes: dry milling,

minimum quantity lubricant (MQL) and high speed

milling. These models will allow us to select the

holistically best process alternative depending on the

specific machining goals. To be able to evaluate a

process alternative from the environmental point of

view we need to develop models of the

corresponding environmental factors, their hierarchy

and their dependencies.

Figure 4: Machine Tool System hierarchy of modeling and

optimization methods and tools.

Environmental factors that are of interest for a green

machine tool are the air quality, the tool wear, the

cutting fluid disposal and the energy consumption

during the various machining steps (setup, tool

changing, workpiece loading, tool approaching and

retracting and machine tool spindle and axes).

Additionally, we need to develop measurement and

monitoring methods and tools to quantitatively

evaluate the magnitude of the environmental factors.

Subsequently we need to develop methods and tools

to transform the environmental factors into

environmental impacts and associated criteria.

Finally we need to develop multi-criteria methods

and tools to be able to evaluate holistically a

machining process across technical, economical and

environmental dimensions. This last objective is

important since environmental performances cannot

be evaluated in isolation but a holistic approach is

needed that considers all the performance aspects

and dimensions. Some criteria would be conflicting

and as a consequence compromise solutions would

be sought with the appropriate choice of the criteria

weights.

At the next level of needed research, we note the

need for the development of process planning

modeling and optimization methods and tools. This

is the point where the life cycle of the machine tool

is crossing with the life cycle of the part. Although

quite a few publications treated systematically this

issue we consider that we still need to do more

research especially with regard to the overall process

plan optimization of a part when several processes

and machine tools are involved. For example we

may be able to reduce the total energy consumption

and environmental impact for the grinding of a

cylindrical part if we first machine the part by

turning with a minimized stock allowance and

reduced dimensional tolerances and subsequently

perform the final grinding of the part (Denkena et al.

, 2005). This beneficial result is expected since it is

well known that the specific cutting energy for

grinding is much bigger than for turning. On the

other hand we need to grind the part to achieve a

high quality part surface. Therefore the goal here is

to develop overall machining strategies for the

manufacture of a part that may involve several

machine tools and alternative machining processes.

Furthermore, even when restricting ourselves to the

use of one machine tool we see the need to develop

methods and tools for the green machining of

complex parts which require complex toolpaths.

This is so since current approaches are in most cases

limited to straight toolpath machining and do not

consider complex curved toolpaths which generally

necessitate the acceleration and deceleration of the

machine tool axes movement and therefore may

impact in an important manner on the total energy

consumption and environmental impact. Therefore,

methods and tools are needed to generated

appropriate toolpaths to reduce the energy

consumption and environmental impacts for

geometrically complex parts.

COMPUTING FOR GREEN MACHINING - Recent Results and Research Perspectives

Another important issue in holistic process

planning optimization is the evaluation of a process

holistically i.e. not only with regard to its part

quality, machining time and cost performance but

also with regard to the expected energy consumption

and environmental impact. It is also desirable to

quantify the total cost of a process plan i.e. to

include the energy consumption cost and

environmental impact reduction or treatment cost. It

is important to emphasize here that the needed

methods and tools would have to model the entire

machine tool system involving the development of

holistic mechatronic machine tool models since we

need to model not only the cutting process, but also

the axes electromechanical feed drives, the spindle

system and its cooling subsystem among others. In

that sense here we use the term process planning in a

broader sense i.e. we include the control aspects that

are needed to achieve these goals.

At the next level of the research vision hierarchy

we need to consider the development of methods

and tools for the modeling and optimization of the

life cycle of a machine tool. Therefore we need such

eco-evaluation methods and tools for each life cycle

phase (design, manufacturing, use, maintenance and

end of life) as a prerequisite. These methods and

tools would probably have to rely on some

experimentally derived databases since it would be

very difficult to model all the related complex

phenomena analytically. Examples of needed

research for the use phase is the need to monitor in

real-time the holistic performance of the machine

tool. This means we need to also monitor and make

transparent to the machine tool user the energy

consumption and environmental impact in real-time

so that he/she may eventually be aware and/or

interfere to improve its energy consumption and

environmental performance. The monitoring

methods and tools could also provide us with

information about the remaining life of the machine

tool and its components so that we can optimize its

maintenance and end-of-life scenarios. For example

on the basis of this information we could develop

models and methods of remanufacturing process

costs and associated environmental impacts for a

used machine tool system. This would be very useful

in reducing the uncertainties that are inherent in

remanufacturing planning and scheduling due to the

arrival of parts with unknown quality and random

quantities. As a result this would significantly

improve the performance of remanufacturing

systems and consequently the recuperation of a great

part of the energy and resource already spent to

manufacture the machine tool or some of its

components.

It is interesting to note here that the eventual

models that we propose to be developed for the life

cycle of machine tool system would also serve in

benchmarking the machine tool systems and in

establishing a holistic rating classifying the machine

tools in different categories according to their

holistic performance. This would be an answer to the

need to develop a green labeling system for machine

tools which is rather difficult to achieve given its

complex performance which strongly also depends

on the way it is used.

At the next step of the hierarchy of needed

research we wish to propose the consideration of the

modeling and optimization of a factory consisting of

several machine tools of different types and the

associated infrastructure. There is recently a strong

research interest in funding research in the area of

the factory of the future and/or the sustainable

factory. These are from our point of view related

issues. The need is to consider here not only the

cycle times, throughput and resource utilization but

also the waste streams in solid, liquid and vapor

states, for part mixes with different material

properties and geometric complexities. Therefore,

here we need to develop modeling and simulation

methods and tools of the extended factory for

planning preventive maintenance and cutting fluid

recycling procedures. We need to generate trade-offs

between reducing the waste stream output and

increasing machine downtime. We also need to

develop new methods and tools for holistically

planning and scheduling a factory with the incoming

arrival of random mixes of various part types with

different geometric complexities.

At the next level of the hierarchy of the needed

research we need to consider the development of

methods and tools for the modeling and optimization

of manufacturing networks consisting of several

machining suppliers geographically distributed. This

involves research issues in evaluating holistically

process plan alternatives between local and global

manufacturing. It also includes part/product

packaging and transportation considerations.

Furthermore, methods and tools are needed for the

modeling of the organization aspects and the

management of global manufacturing networks and

green supply chains. This would necessitate the

development of decision models for incorporating

environmental issues into the problem of supplier

evaluation and selection. Furthermore, we need to

consider the impact of supply chain management

decisions not only on cost, quality, delivery and

INNOV 2010 - International Multi-Conference on Innovative Developments in ICT

technology but also on the environment.

3.2 Energy Consumption Modeling in

Milling of Prismatic Parts

Electricity, before being consumed, is already

burdened with its own environmental ramifications

because its production is accompanied by important

emissions. Therefore, it can be inferred that any

reduction of the energy consumed in machining

yields an environmental benefit.

In this regard, we present here some of our recent

work on energy consumption modeling for the

milling of prismatic parts. This model covers aspects

related to process plan optimization by running

alternative machining strategies and enable the

quantification of the overall energy consumed by the

machine tool system with respect to various use

phase regimes. This example covers the first two

levels in the hierarchy of a machine tool system

presented in Figure 4. Furthermore, this example

also covers one part of the third level modeling in

the manufacturing systems hierarchy: the usage

phase of machine tool modeling.

Figure 5: Information flow and software modules for the

estimation of the energy consumption.

The complete coverage of all the life cycles of a

machine tool is a goal for the future as is the

research on the remaining two levels (fourth and

fifth).

We consider the milling of a prismatic part such

as the one shown in Figure 5.

We will describe the information flow and the

software modules needed in order to model the

energy consumption during the milling of such a

part. The first step is model the three-dimensional

geometry of the part with standard commercial

Computer-aided design systems. Afterwards, we

consider at this stage using the available Computer-

aided facilities in standard commercial systems to

generate the required toolpath to mill the given part.

The output of this modeling would be an APT file in

neutral format containing the description of the

toolpath and the axes feed speeds and spindle speed.

In the future we will consider more general formats

such as the STEP format. The APT file is the main

input to our software that performs the energy

consumption modeling during the milling of the

part.

The first step of the energy modeling software

consists in extracting the detailed toolpath and

speeds information from the APT-file. Afterwards

this becomes an input to our milling energy

consumption module. This module contains detailed

formulas for the estimation of the power

requirements and motion times of the feed axes and

of the spindle with respect to steady state and

accelerating and decelerating regimes. Furthermore,

input from the user to this module is information

about the machine tool characteristics such as its

architectural layout, the moving masses of the axes

the friction coefficient in the guideways, the types of

the spindle bearings and the maximum feed rate.

We also need input data about the cutting tool, the

workpiece and its material, necessary for the

computation of the cutting force components used

for the estimation of the cutting power. Finally we

need data about the auxiliary equipment and their

nominal installed power.

We show in Figure 6 some of our results of the

milling energy consumption for the planar face

feature of the modeled part, machined under wet

conditions and by removing the same amount of

material at two different cutting speeds.

In addition to the energy estimated for the

spindle and axes along the path followed by the tool

for the machining of the planar face with respect to

both steady state and transient regimes, these

graphical representations report also the energy

consumed by the auxiliary equipment of the

monitored machine tool, such as the cutting fluid

pump, the air conditioner of the electrical cabinet,

the hydraulic pump and the tool changer. The energy

consumed by the minimum quantity lubrication

(MQL) system is represented only for the sake of

comparison with its counterpart alternative (i.e.

cutting fluid pump).

The main conclusions which can be drawn from the

analysis of the MTS energy share for the machining

of the planar face at low and high speed levels are as

follows:

(i) for both conditions the power required for

the idle state of the machine generates the

highest energy consumption

(ii) the transient non-cutting movements of the

feed axes do not show appreciable energy

consumption; the acceleration of the

COMPUTING FOR GREEN MACHINING - Recent Results and Research Perspectives

Figure 6: Machine Tool System consumed energy (kJ) for planar face milling (low speed vs. high speed).

Figure 7: Machine Tool System energy consumption (kJ) for part milling (wet vs. dry machining).

Spindle consumes more energy as the

cutting speed increases but it is assumed to

be performed only once at the beginning of

the machining of the milling features of the

part and an important amount of this

energy can be recovered by electrical

braking during spindle deceleration

(ii) The energy consumed to overcome the

mechanical losses of the spindle is

proportional with the speed

(iv) The low spindle speed level employed for

the machining of the planar face proved to

be 36.7 % more energy demanding than

the machining in a higher speed range

If several auxiliary components are used in

parallel during the use phase, the energy required to

fulfill the auxiliary functions of the machining

system can easily become dominant.

Figure 7 shows the difference between the

energy consumed during the milling of the features

depicted in Figure 5 by employing the same cutting

parameters under dry and wet conditions. The

difference mainly stems from the energy required to

run the cutting fluid pump.

INNOV 2010 - International Multi-Conference on Innovative Developments in ICT

4 CONCLUSIONS

We have presented a research vision for the

development of methods and software tools to

support the design and operation of machine tools

while reducing their energy consumption and

environmental impacts. We presented this vision as

a hierarchy of modeling problems to be resolved

starting from the process level, to the process

planning level, to the machine tool life cycle, to the

sustainable factory and finally to the machining

network management. Besides this vision we briefly

presented support the design and operation of

machine tools while reducing their energy

consumption and environmental impacts. We

presented this vision as a hierarchy of modeling

problems to be resolved starting from the process

level, to the process planning level, to the machine

tool life cycle, to the sustainable factory and finally

to the machining network management. Besides this

vision we briefly presented some of our recent work

on energy consumption modeling in milling of

prismatic parts. This modeling allows comparing

process plans with regard to their cutting parameters

and the selected machine tools. Furthermore, it

allows identifying the most important components of

energy consumption in the machine tool so that we

can focus in their optimal design and use.

In this paper we discussed some of our recent

research relative to the first two levels in the

hierarchy of the machine tool system presented in

Figure 4 and a part of the third level. The complete

coverage of all the life cycles of a machine tool

(third level) is a goal for the future as is the research

on the remaining two levels (fourth and fifth).

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COMPUTING FOR GREEN MACHINING - Recent Results and Research Perspectives