A multi-criteria decision method for sustainability assessment of the use phase of machine tool systems

In recent years, going green has become a strategic priority in manufacturing which has evolved from the growing awareness of the need for environmentally friendly processes and products. Recent trends in developing new machining strategies able to support environmental protection and prevention of pollution in balance with socioeconomic needs and technical requirements inevitably require significant efforts in fundamental understanding of the actual energy and material flows needed to meet the machining requirements. This paper describes the methodology and software, Global Reasoning for Eco-Evaluation of Machining, developed to evaluate the use phase of a machine tool system with respect to a consistent set of technical, economical, and environmental criteria, as a part of the NEXT European project. The evaluation, based on the analytic hierarchy process, is conducted at two levels: (a) the process/part level which considers the local cutting environment along with the "actors" that are directly involved in the cutting area, their relationships, and the phenomena that occur from their interactions and (b) the system level which gathers together the main specifications of the machine tool system and the energy requirements associated with various activities performed in order to support the material removal processes. Two database structures were defined in order to store the entire amount of data needed to perform the analysis at each level. A detailed example of the evaluation carried out at the first level demonstrated the superior performance of the dry and minimum quantity lubrication alternatives over their wet machining counterpart when cutting power, cutting fluid consumption, and the machining time were considered as criteria for the performance evaluation of various milling tests.

Machine Tool Use Phase

Ioan Oliver Avram

This thesis is motivated from the fundamental decision problem in today's manufacturing industry which could be summarized as one simple question: how is it possible to achieve economic growth by taking advantage of the latest technologies while protecting the environment? The machine tool has undergone a remarkable change in recent years and the classical concept of an independent, manually operated machine tool, specially dedicated to a particular machining process no longer belongs to the production environment. The increasing usage of computer control and measuring equipment as well as workpiece and tool handling devices has transformed the machine tool into a sophisticated hybrid production system having a lower demand for human supervision of the process. All these efforts are gathered together in order to achieve a high productivity system able to machine different parts respecting quality requirements at the lowest cost. In addition, increasing attention to the environmental and health impacts by governmental regulations and by growing awareness in society is forcing manufacturers to find environmentally friendly designs and machining strategies. The objective of this research is to propose a multicriteria decision aid methodology (MCDA) for evaluation of the use phase of a machine tool system by jointly considering economical, technical and environmental criteria which allows the decision maker to be in a better position to make sustainable decisions. The evaluation is carried out at two levels by addressing the process level with its local cutting area effects and the main activities of the machine tool system by giving full consideration to reduction/elimination of the cutting fluid and reduction of the overall energy consumption. After carefully reviewing previous research, a consistent hierarchical evaluation criteria structure and an entity relationship diagram characterizing the organizational scheme of a database, which stores the data to be used in the evaluation process, is proposed for each level. As a second step, this thesis proposes a model for estimation of the mechanical energy requirements of the cutting subsystem of a machine tool based on the cutter location data, the cutting parameters and the technical specifications of the spindle and feed axes. The MCDA methodology and the energy consumption model were implemented in a software tool using the VBA (Visual Basic for Applications) language and was validated through various tests consisting in the machining of different milling and drilling features of a prismatic part by employing different cutting parameters and cooling/lubrication alternatives. In addition to the cutting tests, an extensive monitoring of the power share amongst the main subsystems of a modern machining center was carried out and a power data collection framework was proposed. The acquisition, interpretation and storage of the experimental data were supported by a measurement platform developed in the LabVIEW environment.

EPFL2010

NC tool path evaluator and generator for high speed milling

Sandeep Dhanik

Milling is a most common type of material removal process by rotating tools to create a variety of features on a part. The material is removed in a controlled way by sweeping a rotating cylindrical tool along the specific trajectory known as milling tool path. For any specified shape and volume of material to be removed, there are a variety of possible tool paths and cutting conditions. These different possibilities can be evaluated based on various geometric as well as process related factors. Milling time is one of the most important factors in evaluating the process efficiency, which depends upon the tool path planning and the behavior of the physical machine tool. Tool path planning usually considers factors such as limitations of cutting tools, tolerance requirement and workpiece geometry etc., which directly influence the milling process time. Further, as milling process involves physical interaction between tool and workpiece, the wear and tear of milling tools is an important issue. As the breakdown of cutting tools is detrimental for productivity; the tool paths must be evaluated based on other important physical considerations like cutting forces and chatter. A number of cutting force models on the preselected cutting parameters with high reliable prediction capability are already available in the literature, however, a simplified category of constant engagement zones are usually assumed to exist. Engagement zone may vary along the tool path as it depends on instantaneous in-process workpiece geometry and hence imparting a change in the cutting forces also. Thus one of the objectives of this work is to present a system to verify a milling process plan to incorporate arbitrary tool paths and in-process changes in workpiece geometry. Among the available tool paths, contour parallel tool paths are the most widely used tool paths for 2D milling operations. A number of exact as well as approximate methods are available for offsetting a closed boundary in order to generate a contour parallel tool path; however, most of methods are inherently incapable of dealing with complex problems (change in topology and self intersecting feature) during offsetting and require highly efficient computational routines to identify and rectify these problems. In this work, a boundary value formulation of the offsetting problem is studied and a fast marching method based solution for tool path generation is presented. This method handles the topological changes during offsetting naturally and deals with the generation of discontinuities in the slopes by including an "entropy condition" in its numerical implementation. A number of examples are presented and computational issues are discussed for tool path generation. Although, the tool path generation methods discussed earlier guarantee to generate a geometrically feasible tool path the in-process engagement is still not constant or its variation is not minimized. This leads to variation of actual radial depth of cut especially at the sharp corners or high curvature profiles, the usual problems encountered due to this variation are (i) left over material at corners (ii) sudden increment in cutting forces. These conditions force the process planner to add more tool passes to the original tool paths or adhere to conservative feed values respectively. In either case, it renders the process plan inefficient. This work presents a method based on signed distance function to generate spiral-out contour parallel tool path generation. This proposed method and algorithms avoids the leftover material at the corners and minimizes the variation of radial depth of cut at each level of contour milling and consequently maintains the same cutting conditions specified as starting cutting parameters which are favorable for process reliability, part quality and tool life. Finally the second type of contour parallel tool path i.e. spiral-in milling is investigated for milling tool path generation with an aim to generate "efficient" geometrically feasible spiral in tool paths which minimize the variation of the milling process from its steady state while minimizing the curvature of the tool path. Further, the tool path for non-convex geometry are developed which are optimized for the stepover and the engagement with no tool retraction involved, which is highly desirable for high speed milling of arbitrary pockets.

EPFL2009

Modeling and Simulation of Energy Efficient Milling Process Plans for Prismatic Parts

Nenad Nesic

The milling process has been continuously optimized from many aspects: forces, velocities, stability, quality. Numerous papers have been published that report results in the domain of toolpath optimization with criteria such as raising the quality of the machined part, obtaining a stable machining process and maximizing the material removal rate. However, only recently researchers have started investigating the ecological impact of machining processes. With the constantly increasing prices of electrical energy and all environmental problems caused by the production and waste of the energy, it has become indispensable to look for ways to optimize machining processes from the energy consumption aspect, too. It is in this domain, then, that the work described in this dissertation contributes – to add a new criterion for the sustainable operation of machine tools: reducing the energy consumption during the use phase of the machine tool. The total energy spent in a machining process is the sum of power spent by all machine tool subsystems multiplied by the time that they are working. Therefore, the operating strategies for increasing energy efficiency for the high-speed machining processes must be oriented towards the reduction of the total machining time (productive and unproductive) and reduction of instantaneous consumed power in the machining process or, preferably, both. There are many causes for milling process time and energy inefficiency. The major sources of potential time reductions include: (i) the issues related to the geometry and topology of the toolpath („air-time”, overlapping segments, gouge and uncut regions, orientation of the toolpath), (ii) the issues related to the kinematics of the feed drives (the feed velocity/acceleration profile). The possible domains for power consumption reduction are related to the forces that exist in the machining process (cutting, inertial, gravitational and friction forces). The power invested to overcome the cutting force is necessary for the machining process but its consumption should be optimized through constant cutting engagement and feedrate scheduling strategies. The other forces are responsible for the pure mechanical power loss and they should be minimized. The optimization variables for inertial and gravitational forces include the feed motion profile and moving mass configuration, while friction losses are load and/or velocity dependent. In addition, there are some power losses in the electric components of machine tool drives (electrical power losses), whose dependency on velocity and mechanical load can also be modeled. Despite many research efforts to analyze and model the phenomena causing inefficiency of the machining process, they are usually not taken into account during milling process planning. In fact, rare are the attempts to use this knowledge to optimize the milling process with more than one of the above mentioned criteria. The reason for that lies in the fact that increasing the instantaneous values of tool engagement and feedrate in order to minimize total machining time also increases the consumed power and, indirectly, deteriorates the tool and/or destabilizes the cutting process. The existence of conflicting criteria in the objective functions imposes the use of evolutionary algorithms for multiobjective optimization. The process of experimental validation of such an optimization model requires costly and complex external hardware setup and it is also time consuming. Hence, there is an emerging need for the development of an accurate model, which would be used for the simulation of the milling process and testing the competing optimization strategies. The ultimate goal of contemporary manufacturing science and engineering is the development of a holistic virtual machine tool system. The motivation of this PhD research is to contribute to this objective by developing the “virtual milling process for prismatic parts (produced by 2.5D milling)”. This category of objects is selected, because the majority of CNC milling tasks can be performed using 2.5D milling. A very large number of mechanical parts are prismatic (their geometry consists exclusively of features that represent 2D contours extruded in a perpendicular direction). Parts that are even more complex are usually produced from a blank by a 2.5D roughing and 3D–5D finishing. Therefore, development of an accurate model of a 2.5D milling process represents a significant contribution to manufacturing engineering. Starting with above given problem description, we have defined the following research objectives: 1. Model power and energy consumption of a 2.5D milling machine as a function of the toolpath geometry (curvature and continuity), cutting engagement, real feedrate profiles and spindle rotational speed, taking into account moving mass configuration, all power losses (mechanical and electrical) in feed-axis and spindle drives and electromechanical constraints of servo drives; 2. Design an integrated software environment for simulation of the developed models; 3. Validate the model experimentally; 4. Demonstrate the potential of its use for multi-objective process optimization. Cutting engagement calculation is performed by using two competing methodologies, in order to make a comparison of their performances. The first one, the pixel based method, is based on discrete image processing, while the other, the exact method, is based on Boolean operations and vector geometry. The tests performed in more than 20 feature/toolpath combinations demonstrate that the exact method is more precise whereas the pixel-based method is computationally much faster. The machine tool operator commands a constant feedrate value. During the process, based on his/her subjective judgment, he/she can manually tune it to keep the process in the desired boundaries. One of the objectives of this research is to predict the real feedrate values so that they can be integrated in the part program before the process start. The feasible profiles of feed velocities for each toolpath segment are analyzed by answering the following questions: can the commanded feedrate be achieved and with what sequence of acceleration and deceleration phases, how much the tool has to slow down in corners and how does the feedrate profile degenerate in segments where the commanded feedrate cannot be reached? In order to determine all forces and torques, a machine tool model is developed. The following subsystems are modeled as rigid bodies (without vibrations): feed motor shaft, transmission, lead screw/nut pair, lead screw bearings, guides (sliding and rolling design), table with the workpiece and electrospindle (rotor, stator and bearings). All kinetic variables (linear and angular speeds; cutting, inertial and friction forces and torques) are then calculated in the joints of this multi-body system. The modeling of all speeds, forces and torques that occur in the machine tool system during the machining process, allows for calculation of various indicators of process time and energy efficiency: material removal rate, total machining time, useful power (invested in cutting), power loss due to the friction in the joints, power losses in electrical motors, electrical energy consumption of feed and spindle drives. In order to assess the accuracy and the reliability of the developed model two sets of experiments have been performed. The model validation is performed on several subsystem levels and the simulation results show a very good compliance with the experimental results. The first experimental setup consists of the force dynamometer, to measure cutting force components in linear axis directions, two laser optical position sensors, to measure the real feedrate and the power sensor, to measure the total power consumption of the machine tool electrical motors. The machining process was performed on the 6-axis machining center C.B. Ferrari A152 and the data acquisition platform was developed in LabVIEW 2010. The second experimental setup consists of the torque dynamometer, to measure the cutting torque directly on the spindle, the built-in current sensor that measures the motor current proportional to the electrical power consumed by the spindle and, again, the power sensor, to measure the total power consumption of the machine tool electrical motors. This time, MIKRON HPM 600U, a 5-axis milling machine equipped with the controller iTNC530, was used for the experimentation. The developed model is ready for practical implementation. Several examples have been prepared to demonstrate its capabilities in the domains of milling process simulation, sensitivity analysis and prospective optimization strategies. These examples include the prediction of various kinetostatic variables for given toolpaths, choice of the optimum machining strategy (minimization of machining time, moving mass and energy consumption) and process optimization by feedrate scheduling (reduction of cutting force fluctuation). As a conclusion, the major contribution of this PhD research is the development of a comprehensive rigid-body dynamics model of a machine tool system, aimed for the generation, simulation and optimization of 21⁄2D milling process plans. The model features several novelties compared to existing approaches: (i) it takes into account the machine tool rigid body dynamics and real tool kinematics in toolpath planning, (ii) it predicts all mechanical and electrical power losses in the machine tool system (iii) it allows the modeling of machine tool system electromechanical constraints. The model was experimentally validated on two real machine tools in different workshops and its capabilities for the simulation of different toolpath patterns and optimization of process parameters were successfully demonstrated using several examples.

EPFL2012