Prior to the period known as the Industrial Revolution (1750), the skill of the workers determined good mechanical construction. Each machine was a work of craftsmanship and its quality depended directly on skill and experience.

After the period of the Industrial Revolution, production changed towards large series manufacturing. Appearance of parts manufactured independently and assembled or assembled together to form the final product, since it is impossible to manufacture a part with an exact nominal dimension, the term Tolerance appears.

Machines have greater importance in manufacturing/production (more perfection) and the influence of the operator's skill decreases. Currently, with the most modern machines, the operator only has the function of controlling and feeding them. The need for control over the production process demanded, at the same time, the evolution of measurement systems (the caliper appeared in 1840 and between 1870-1880 the screw micrometer or Palmer, the use of calipers spread from 1880 and replaced the measurement of a dimension by comparison with a fixed dimension.

With new products, increasingly complex mechanical systems are created in which many factors intervene that increasingly determine variability and influence capacity. Need to define a target value and its margin of variability (normalized) called Tolerances (Dimensional, Shape, Position, Orientation). Maintain consistency between tolerance/capacity/manufacturing cost, since it makes no sense to assign tolerances that cannot be obtained with the capabilities of the manufacturing processes and equipment, with the measurement techniques and equipment, and with the established regulation and control procedures.

The latest trends in the evolution of tool materials establish hard metal cores with coatings of titanium carbides or nitrides deposited by precipitation through chemical reactions in a gaseous state that give rise to layers of about 0.005 mm.

In a second generation of coated carbide tools, this has a treatment to create a diffusion zone under the deposited layer and allow a gradual variation of properties between the internal base and the external layer (differences in elasticity and expansions).

Coated with a double layer of outer aluminum on a TiC support layer.

Contenido

A continuación se explican los diferentes tipos de desgaste según el fenómeno que actúa:.

Abrasive wear.

It is due to the harder particles, included in the material to be machined or in the increased edge given by high deformation rates of hard material, and occurs on the incidence face of the cutting tool.

High hardness inclusions must be taken into account because they can cause scratches on the tool. These scratches may not be parallel to the chip flow direction due to numerous aspects. Valid for steels and cast irons and establishes that wear is not caused by mechanical abrasion.

Diffusion wear.

It occurs between temperatures of 900 and 1200 °C, so it is not important for carbon steel and high-speed steel tools, which cannot work at these temperatures. On the other hand, in those made of hard metal, ceramics or boron nitride, the atomic mobility increases and a mutual dissolution of the material of the piece and that of the tool occurs. The activity of this process increases with the cutting speed. Hence, diffusive wear can be considered as a chemical wear that produces variations in the surface layer of the tool and thus compromises its wear resistance.

Oxidation wear.

It is located on the contours of the contact region between the piece and the tool, and is characterized by having a temper color. It depends on the material of the tool and the working temperatures. For steel tools it is not of great importance, since they do not normally work at high temperatures, while in tungsten-based hard metal tools, due to the temperatures and the oxygen existing in the atmosphere, a layer of complex oxides based on tungsten, cobalt and iron forms on the surface of the tool, which has a certain destructive action on the hard metal structure. This action is especially observed on the secondary cutting edge, where wrinkles appear that can cause breakage of the tool tip.

Fatigue wear.

It is frequently a thermo-mechanical combination. The fluctuation in temperature and the alternating action of cutting forces can cause cracking and even breakage in the cutting edges. The action of intermittent cutting leads to continuously generating alternative heating that causes thermal shocks on the cutting edges. Some tool materials are more sensitive than others to mechanical fatigue. Pure mechanical fatigue can also come from cutting forces, sometimes being quite high for the strength of the cutting edge. This can happen in the presence of hard or very tough workpiece materials, very high feed ranges, or when the tool material is not hard enough. However, in these cases plastic deformation predominates.

Adhesive wear.

The adhesion phenomenon occurs at temperatures below 900 °C and is inversely proportional to the hardness of the tool. It is due to the presence of high temperatures and cutting pressures, also to the fact that the inner surface of the chip is clean and without a protective oxide layer and therefore chemically very active. An inverse form of this phenomenon is the contribution edge (regrown edge). When part of the chip remains adhered to the edge of the tool due to temperature, pressure and contact time, adhesion initially increases with speed, as temperatures are reached that favor this phenomenon, but at high speeds the temperature increases to the point that it softens the adhered particles and facilitates their detachment without affecting the tool material since it is much more resistant.

Cada uno de los mecanismos de desgaste que se han analizado anteriormente, influyen de forma conjunta en el filo de la herramienta de corte. De esta manera se materializan en el mismo a través de diversas manifestaciones entre las cuales podemos diferenciar.

Wear of incidence flanks.

This wear takes place on the flanks of the edge, mainly due to the phenomenon of abrasion wear. Excessive flank wear will lead to a worsening of surface quality, deterioration of dimensional accuracy and increased friction as a consequence of geometric transformation.

Crater wear.

It occurs on its face and may be due to abrasion and diffusion wear phenomenon. The crater is generated by the detachment of particles from the tool material, taking place on the detachment face of the tool. It can also be caused by the sharpening effect caused by the hard particles or by the diffusion action of the hot part of the chip face in contact with the tool and its material. The high hardness, hot hardness and minimum affinity between materials minimize the tendency to crater wear. Excessive crater wear modifies the cutting geometry of the tool and can lead to poor chip formation, also changing the directions of the cutting force and weakening the cutting edge of the tool.

Wear due to plastic deformation.

It occurs as a result of the combination of high temperatures and pressures on the cutting edge. High cutting speeds, high feeds and hard workpiece materials result in compression and heat. Maintaining hot hardness is essential for the stability of the tool material and thus avoiding plastic deformation. The typical bulging of the cutting edge will cause, at high temperatures, geometric deformation, chip flow deviations and will continue until reaching a critical state. The size of the edge reinforcement and the geometry of the cut are of great importance to combat this type of tool deterioration.

Wear in the form of a chip.

It is a typical wear due to adhesion but it can also be formed due to the oxidation phenomenon. The dent can form on the cutting edge due to a part of the material, thus locating the wear at the end of the cutting depth where the air comes into contact with the cutting area. This wear spreads across the cutting edge in a mechanical manner in hard materials. An excessive wear chip affects the quality of the surface finish and eventually causes a weakening of the cutting edge.

Wear due to thermal cracks.

The cracks are mainly due to fatigue wear as a consequence of a thermal cycle; especially due to temperature changes that occur in an alternative cut such as milling and that can give rise to this type of wear. The arrangement of the cracks, perpendicular to the cutting edge, means that particles can be released. These particles, from the tool material, can themselves become a risk that help destroy the cutting edge itself.

Cracks due to mechanical fatigue.

They can occur when the impact of cutting forces is excessive. This fracture is due to the continuous variation in the load on the tool where, by itself, it is not large enough to cause fracture. The start of the cut and the variations in the magnitude of the forces and direction may be too much for the strength and toughness of the tool. These forces occur mainly in the direction of the cutting edge.

Wear due to chipping of the cutting edge.

It occurs when the edge of the cut breaks rather than wears out. This fatigue, usually from alternating loading cycles, causes the particles of the tool material to scratch the surface of the material from which they come. Intermittent cutting is frequently the cause of this type of wear. Careful inspection of the cutting edge will indicate when chipping or wear of the leading edge occurs. Microfracturing and chipping are variants of this type of edge destruction.

Fracture wear.

It can be a catastrophic end to the blade. A high degree of deterioration is the most damaging and should be avoided whenever possible. Edge breakage is often the end of the line to other processes or types of wear. The change in geometry, the weakening of the cutting edge and the increase in temperatures and forces will eventually lead to further destruction of the cutting edge, with strong cutting data or since the demand for workpiece material may be the result of various stress factors on the tool material unable to cope with the operational demand.

Formation of the contribution edge.

It is also known as a regrown edge. It is mostly related to the temperature and cutting speed, in relation to the phenomenon it can also be the result of a very soft material on the part and other types of wear. This is negative for the cutting edge, as well as the change in its geometry and the particles of the tool material themselves that can be welded with the material of the piece, giving shape to the agglomerate of the edge. The affinity between the part and tool materials plays an important role, as well as the low temperatures and low pressures that will lead to the welding condition of the chip material with the tool attack surface.

In most situations where control charts are used, the focus is on statistical process control, reduction of variability, and continuous process improvement.

The modified control charts are used to analyze the behavior of the different processes and to predict possible production failures using statistical methods. These are used in most industrial processes, such as tool wear control.

In the control process of industrial tools a high degree of capacity is achieved, it is advisable to reduce the level of control provided by the standard control charts, for this we will use the modified control limits.

Modified control limits for the Xmean are used when Cp or Cpk is much greater than 1, that is, when the process variability is much less than the extent of the limits.

The interest in the modified control chart is restricted to detecting whether the location of the true process mean μ is such that the process is producing a nonconforming fraction in excess of a specified value δ. In fact, μ is allowed to vary over an interval. The mean can be moved, both higher by µU and lower by µL, by a value such that the probability of being out of specifications is δ; within these limits of variability the process will be in a state of control.

The initial tool setting is at some multiple of σx above the lower specification limit and the maximum allowable process average is at the same multiple of σx below the upper specification limit.

To specify the control limits of a modified chart, it will be assumed that the output of the process has a normal distribution. For the non-conforming fraction of the process to be less than δ, we will take into account that the value of the average has to be between µU and µL, they can be calculated using:.

μL = LSL + Zδσ.

μU = USL + Zδσ.

where Zδ is the upper 100(1-α) percentage point of the standard normal distribution.

For a good control chart design, a good estimate of σ must be available. If the process variability is shifted (variability in the process changes), modified control limits will not be appropriate; an estimate of σ would usually be obtained from an R chart or an S chart.

Los métodos más utilizados hoy en día para cuantificar el desgaste en herramientas de corte son:.

Measurement of the surface roughness of machined parts.

Roughness is the result of irregularities produced on the surface of a part by the chip removal action of a cutting tool and the material of the part. This roughness influences such important factors as resistance to wear, fatigue, corrosion and the total cost of the part, since obtaining a high-quality surface increases the cost.

To evaluate the values ​​of the irregularities, the roughness meter is used, which is a device that tracks the profile in a straight line, using a fine tip called a probe and that translates the variations in surface height into electrical signals that are recorded and processed in a control unit. Different roughness parameters are calculated from these signals. The most important surface state parameters that describe irregularities and that have been analyzed are: Ra, Rq, Rt, Rc, Rz, and Rsm.

In order to understand the meaning of these surface parameters, the meaning of the equivalent sampling length (cutt off) and the evaluation length will be explained. Roughness meters usually work at equivalent sampling lengths of 0.08, 0.25, and 2.5mm, which is the necessary length from which the signals are integrated and the parameters can be calculated. The probe performs a sampling of the evaluation length, which is the equivalent sampling length times a cutt off number, between 1 and 5. The screen shows as a result the average of the results obtained in each equivalent sampling length or the maximum for the entire evaluation length, depending on each parameter.

Wear monitoring.

Tool wear monitoring systems (SMDH) have been developed in recent years by different research groups, although it must be said that most of this research has remained in the academic field and has not reached the industry.

These systems can be classified into two groups, those that use direct methods and those that use indirect methods. The direct ones are based on the direct measurement of tool wear. Optical methods, radioactive and electrical resistance methods, artificial vision methods, etc. are used in its development. These methods have the advantage of high precision, but however, their effectiveness is limited in real applications. These limitations may be due, for example, to the fact that they cannot provide a measurement without interrupting the lubrication, or simply due to chip egress that can prevent the measurement. For all this, SMDHs based on direct methods may not be considered as wear monitoring systems as such, since said wear measurement cannot occur continuously over time.

Indirect SDMH are based on the relationship between cutting conditions, features extracted from some signals acquired during the process, and tool wear. In these systems the signals that have been used are very diverse. These include cutting forces, vibrations, acoustic emission, temperature, etc. However, only a few indirect SMDHs have been applied in industrial settings. This is probably because tool wear is a complex phenomenon that occurs in different and varied ways in metal cutting processes. Furthermore, the nature of the monitored signals can be considered stochastic and non-stationary. This nature – which may be due to the heterogeneities of the part, the sensitivity of the features measured in the process to changes in cutting conditions, and the non-linear relationship of these features with tool wear – makes the development of an indirect SMDH non-trivial.

The development of an SMDH includes three stages:

Once the monitoring signals are chosen, the fundamental problem to achieve an effective SMDH involves the extraction of information well correlated with wear. This purpose is not simple, due to the stochastic and non-stationary nature of the signals acquired in the process, as discussed above. According to some of the latest research, this is most likely the most important stage in the development of an SMDH. In fact, much of the efforts currently dedicated to this field of research are linked to the use of new techniques and methods to extract information from the signals acquired in the process that are well correlated with wear. Some of these techniques are: time series or wavelet analysis. In the last phase of the development of an SMDH, artificial intelligence is being used massively. Specifically, artificial neural networks, since their robustness to disturbances in the input information, makes them ideal for the development of SMDHs.

The development of SMDHs is still in an initial phase. In fact, even today there are no SMDHs whose practical usefulness is completely valid. Although there are many publications on the subject, it is also worth saying that a priority line of research has not yet been established, nor have the guidelines to be followed for the design of these systems been set. However, although the ideal would be to use only an indirect method, it seems that finally a direct and an indirect method will be used in the same monitoring system.

Wear measurement performed with a direct method is more reliable than that performed with an indirect method. However, an online wear estimate can only be performed using an indirect method. In short, it seems appropriate to design these systems making use of the synergy produced by using both methods. In any case, an economic criterion must be taken into account, since some of the systems that have been developed in the university environment, although with high benefits, involve an investment that makes them unviable in practice.

To optimize the cost of an SDMH, it is evident that the smallest number of signals must be used, without reducing the reliability of the system. This is an issue that is being taken into account in current research. In fact, of the three phases of the development of an SMDH it seems that currently research has focused on the extraction of information from the monitored signals as a basis for optimizing these systems. In this way, being able to obtain more information about the status of the tool with a smaller number of signals reduces system costs.

An order of type KLM-45, pulleys for refineries, is desired to be manufactured, as shown in the plan. The material used is an austenitic stainless steel alloy DIN 1.4418 (X4 Cr Ni Mo 16-5) with a verified Brinell 195 HB hardness. To manufacture it, it is started from alloy ingots that are melted in a crucible and molded.

The cutting conditions for boring are:.

GC4235 Carbide Tool

Tool release angle γTM = 5º

Main position angle χTM = 75°

Advance speed in work fnTM = 0.3 mm/rev.

TTM cutting speed= 30 min.

During the manufacturing of the batch of type KLM-45, the GC4235 carbide tool will suffer progressive wear that can be seen in the surface finishes of the finished pieces. It will not be possible to manufacture the complete batch with a single tool, taking into account that the useful life of the tool will be directly related to the cutting parameters and materials used established in the problem statement.

The modified control chart analyzes the behavior of the process and can predict possible tool failures using statistical methods.

The initial setting of the tool is within the 6σ interval of the normal distribution close to the lower limit of the specification. As the tool wears out, the variability of the process will change, bringing the process closer to the upper limit of the specification.

Prior to the period known as the Industrial Revolution (1750), the skill of the workers determined good mechanical construction. Each machine was a work of craftsmanship and its quality depended directly on skill and experience.

After the period of the Industrial Revolution, production changed towards large series manufacturing. Appearance of parts manufactured independently and assembled or assembled together to form the final product, since it is impossible to manufacture a part with an exact nominal dimension, the term Tolerance appears.

Machines have greater importance in manufacturing/production (more perfection) and the influence of the operator's skill decreases. Currently, with the most modern machines, the operator only has the function of controlling and feeding them. The need for control over the production process demanded, at the same time, the evolution of measurement systems (the caliper appeared in 1840 and between 1870-1880 the screw micrometer or Palmer, the use of calipers spread from 1880 and replaced the measurement of a dimension by comparison with a fixed dimension.

With new products, increasingly complex mechanical systems are created in which many factors intervene that increasingly determine variability and influence capacity. Need to define a target value and its margin of variability (normalized) called Tolerances (Dimensional, Shape, Position, Orientation). Maintain consistency between tolerance/capacity/manufacturing cost, since it makes no sense to assign tolerances that cannot be obtained with the capabilities of the manufacturing processes and equipment, with the measurement techniques and equipment, and with the established regulation and control procedures.

The latest trends in the evolution of tool materials establish hard metal cores with coatings of titanium carbides or nitrides deposited by precipitation through chemical reactions in a gaseous state that give rise to layers of about 0.005 mm.

In a second generation of coated carbide tools, this has a treatment to create a diffusion zone under the deposited layer and allow a gradual variation of properties between the internal base and the external layer (differences in elasticity and expansions).

Coated with a double layer of outer aluminum on a TiC support layer.

Contenido

A continuación se explican los diferentes tipos de desgaste según el fenómeno que actúa:.

Abrasive wear.

It is due to the harder particles, included in the material to be machined or in the increased edge given by high deformation rates of hard material, and occurs on the incidence face of the cutting tool.

High hardness inclusions must be taken into account because they can cause scratches on the tool. These scratches may not be parallel to the chip flow direction due to numerous aspects. Valid for steels and cast irons and establishes that wear is not caused by mechanical abrasion.

Diffusion wear.

It occurs between temperatures of 900 and 1200 °C, so it is not important for carbon steel and high-speed steel tools, which cannot work at these temperatures. On the other hand, in those made of hard metal, ceramics or boron nitride, the atomic mobility increases and a mutual dissolution of the material of the piece and that of the tool occurs. The activity of this process increases with the cutting speed. Hence, diffusive wear can be considered as a chemical wear that produces variations in the surface layer of the tool and thus compromises its wear resistance.

Oxidation wear.

It is located on the contours of the contact region between the piece and the tool, and is characterized by having a temper color. It depends on the material of the tool and the working temperatures. For steel tools it is not of great importance, since they do not normally work at high temperatures, while in tungsten-based hard metal tools, due to the temperatures and the oxygen existing in the atmosphere, a layer of complex oxides based on tungsten, cobalt and iron forms on the surface of the tool, which has a certain destructive action on the hard metal structure. This action is especially observed on the secondary cutting edge, where wrinkles appear that can cause breakage of the tool tip.

Fatigue wear.

It is frequently a thermo-mechanical combination. The fluctuation in temperature and the alternating action of cutting forces can cause cracking and even breakage in the cutting edges. The action of intermittent cutting leads to continuously generating alternative heating that causes thermal shocks on the cutting edges. Some tool materials are more sensitive than others to mechanical fatigue. Pure mechanical fatigue can also come from cutting forces, sometimes being quite high for the strength of the cutting edge. This can happen in the presence of hard or very tough workpiece materials, very high feed ranges, or when the tool material is not hard enough. However, in these cases plastic deformation predominates.

Adhesive wear.

The adhesion phenomenon occurs at temperatures below 900 °C and is inversely proportional to the hardness of the tool. It is due to the presence of high temperatures and cutting pressures, also to the fact that the inner surface of the chip is clean and without a protective oxide layer and therefore chemically very active. An inverse form of this phenomenon is the contribution edge (regrown edge). When part of the chip remains adhered to the edge of the tool due to temperature, pressure and contact time, adhesion initially increases with speed, as temperatures are reached that favor this phenomenon, but at high speeds the temperature increases to the point that it softens the adhered particles and facilitates their detachment without affecting the tool material since it is much more resistant.

Cada uno de los mecanismos de desgaste que se han analizado anteriormente, influyen de forma conjunta en el filo de la herramienta de corte. De esta manera se materializan en el mismo a través de diversas manifestaciones entre las cuales podemos diferenciar.

Wear of incidence flanks.

This wear takes place on the flanks of the edge, mainly due to the phenomenon of abrasion wear. Excessive flank wear will lead to a worsening of surface quality, deterioration of dimensional accuracy and increased friction as a consequence of geometric transformation.

Crater wear.

It occurs on its face and may be due to abrasion and diffusion wear phenomenon. The crater is generated by the detachment of particles from the tool material, taking place on the detachment face of the tool. It can also be caused by the sharpening effect caused by the hard particles or by the diffusion action of the hot part of the chip face in contact with the tool and its material. The high hardness, hot hardness and minimum affinity between materials minimize the tendency to crater wear. Excessive crater wear modifies the cutting geometry of the tool and can lead to poor chip formation, also changing the directions of the cutting force and weakening the cutting edge of the tool.

Wear due to plastic deformation.

It occurs as a result of the combination of high temperatures and pressures on the cutting edge. High cutting speeds, high feeds and hard workpiece materials result in compression and heat. Maintaining hot hardness is essential for the stability of the tool material and thus avoiding plastic deformation. The typical bulging of the cutting edge will cause, at high temperatures, geometric deformation, chip flow deviations and will continue until reaching a critical state. The size of the edge reinforcement and the geometry of the cut are of great importance to combat this type of tool deterioration.

Wear in the form of a chip.

It is a typical wear due to adhesion but it can also be formed due to the oxidation phenomenon. The dent can form on the cutting edge due to a part of the material, thus locating the wear at the end of the cutting depth where the air comes into contact with the cutting area. This wear spreads across the cutting edge in a mechanical manner in hard materials. An excessive wear chip affects the quality of the surface finish and eventually causes a weakening of the cutting edge.

Wear due to thermal cracks.

The cracks are mainly due to fatigue wear as a consequence of a thermal cycle; especially due to temperature changes that occur in an alternative cut such as milling and that can give rise to this type of wear. The arrangement of the cracks, perpendicular to the cutting edge, means that particles can be released. These particles, from the tool material, can themselves become a risk that help destroy the cutting edge itself.

Cracks due to mechanical fatigue.

They can occur when the impact of cutting forces is excessive. This fracture is due to the continuous variation in the load on the tool where, by itself, it is not large enough to cause fracture. The start of the cut and the variations in the magnitude of the forces and direction may be too much for the strength and toughness of the tool. These forces occur mainly in the direction of the cutting edge.

Wear due to chipping of the cutting edge.

It occurs when the edge of the cut breaks rather than wears out. This fatigue, usually from alternating loading cycles, causes the particles of the tool material to scratch the surface of the material from which they come. Intermittent cutting is frequently the cause of this type of wear. Careful inspection of the cutting edge will indicate when chipping or wear of the leading edge occurs. Microfracturing and chipping are variants of this type of edge destruction.

Fracture wear.

It can be a catastrophic end to the blade. A high degree of deterioration is the most damaging and should be avoided whenever possible. Edge breakage is often the end of the line to other processes or types of wear. The change in geometry, the weakening of the cutting edge and the increase in temperatures and forces will eventually lead to further destruction of the cutting edge, with strong cutting data or since the demand for workpiece material may be the result of various stress factors on the tool material unable to cope with the operational demand.

Formation of the contribution edge.

It is also known as a regrown edge. It is mostly related to the temperature and cutting speed, in relation to the phenomenon it can also be the result of a very soft material on the part and other types of wear. This is negative for the cutting edge, as well as the change in its geometry and the particles of the tool material themselves that can be welded with the material of the piece, giving shape to the agglomerate of the edge. The affinity between the part and tool materials plays an important role, as well as the low temperatures and low pressures that will lead to the welding condition of the chip material with the tool attack surface.

In most situations where control charts are used, the focus is on statistical process control, reduction of variability, and continuous process improvement.

The modified control charts are used to analyze the behavior of the different processes and to predict possible production failures using statistical methods. These are used in most industrial processes, such as tool wear control.

In the control process of industrial tools a high degree of capacity is achieved, it is advisable to reduce the level of control provided by the standard control charts, for this we will use the modified control limits.

Modified control limits for the Xmean are used when Cp or Cpk is much greater than 1, that is, when the process variability is much less than the extent of the limits.

The interest in the modified control chart is restricted to detecting whether the location of the true process mean μ is such that the process is producing a nonconforming fraction in excess of a specified value δ. In fact, μ is allowed to vary over an interval. The mean can be moved, both higher by µU and lower by µL, by a value such that the probability of being out of specifications is δ; within these limits of variability the process will be in a state of control.

The initial tool setting is at some multiple of σx above the lower specification limit and the maximum allowable process average is at the same multiple of σx below the upper specification limit.

To specify the control limits of a modified chart, it will be assumed that the output of the process has a normal distribution. For the non-conforming fraction of the process to be less than δ, we will take into account that the value of the average has to be between µU and µL, they can be calculated using:.

μL = LSL + Zδσ.

μU = USL + Zδσ.

where Zδ is the upper 100(1-α) percentage point of the standard normal distribution.

For a good control chart design, a good estimate of σ must be available. If the process variability is shifted (variability in the process changes), modified control limits will not be appropriate; an estimate of σ would usually be obtained from an R chart or an S chart.

Los métodos más utilizados hoy en día para cuantificar el desgaste en herramientas de corte son:.

Measurement of the surface roughness of machined parts.

Roughness is the result of irregularities produced on the surface of a part by the chip removal action of a cutting tool and the material of the part. This roughness influences such important factors as resistance to wear, fatigue, corrosion and the total cost of the part, since obtaining a high-quality surface increases the cost.

To evaluate the values ​​of the irregularities, the roughness meter is used, which is a device that tracks the profile in a straight line, using a fine tip called a probe and that translates the variations in surface height into electrical signals that are recorded and processed in a control unit. Different roughness parameters are calculated from these signals. The most important surface state parameters that describe irregularities and that have been analyzed are: Ra, Rq, Rt, Rc, Rz, and Rsm.

In order to understand the meaning of these surface parameters, the meaning of the equivalent sampling length (cutt off) and the evaluation length will be explained. Roughness meters usually work at equivalent sampling lengths of 0.08, 0.25, and 2.5mm, which is the necessary length from which the signals are integrated and the parameters can be calculated. The probe performs a sampling of the evaluation length, which is the equivalent sampling length times a cutt off number, between 1 and 5. The screen shows as a result the average of the results obtained in each equivalent sampling length or the maximum for the entire evaluation length, depending on each parameter.

Wear monitoring.

Tool wear monitoring systems (SMDH) have been developed in recent years by different research groups, although it must be said that most of this research has remained in the academic field and has not reached the industry.

These systems can be classified into two groups, those that use direct methods and those that use indirect methods. The direct ones are based on the direct measurement of tool wear. Optical methods, radioactive and electrical resistance methods, artificial vision methods, etc. are used in its development. These methods have the advantage of high precision, but however, their effectiveness is limited in real applications. These limitations may be due, for example, to the fact that they cannot provide a measurement without interrupting the lubrication, or simply due to chip egress that can prevent the measurement. For all this, SMDHs based on direct methods may not be considered as wear monitoring systems as such, since said wear measurement cannot occur continuously over time.

Indirect SDMH are based on the relationship between cutting conditions, features extracted from some signals acquired during the process, and tool wear. In these systems the signals that have been used are very diverse. These include cutting forces, vibrations, acoustic emission, temperature, etc. However, only a few indirect SMDHs have been applied in industrial settings. This is probably because tool wear is a complex phenomenon that occurs in different and varied ways in metal cutting processes. Furthermore, the nature of the monitored signals can be considered stochastic and non-stationary. This nature – which may be due to the heterogeneities of the part, the sensitivity of the features measured in the process to changes in cutting conditions, and the non-linear relationship of these features with tool wear – makes the development of an indirect SMDH non-trivial.

The development of an SMDH includes three stages:

Once the monitoring signals are chosen, the fundamental problem to achieve an effective SMDH involves the extraction of information well correlated with wear. This purpose is not simple, due to the stochastic and non-stationary nature of the signals acquired in the process, as discussed above. According to some of the latest research, this is most likely the most important stage in the development of an SMDH. In fact, much of the efforts currently dedicated to this field of research are linked to the use of new techniques and methods to extract information from the signals acquired in the process that are well correlated with wear. Some of these techniques are: time series or wavelet analysis. In the last phase of the development of an SMDH, artificial intelligence is being used massively. Specifically, artificial neural networks, since their robustness to disturbances in the input information, makes them ideal for the development of SMDHs.

The development of SMDHs is still in an initial phase. In fact, even today there are no SMDHs whose practical usefulness is completely valid. Although there are many publications on the subject, it is also worth saying that a priority line of research has not yet been established, nor have the guidelines to be followed for the design of these systems been set. However, although the ideal would be to use only an indirect method, it seems that finally a direct and an indirect method will be used in the same monitoring system.

Wear measurement performed with a direct method is more reliable than that performed with an indirect method. However, an online wear estimate can only be performed using an indirect method. In short, it seems appropriate to design these systems making use of the synergy produced by using both methods. In any case, an economic criterion must be taken into account, since some of the systems that have been developed in the university environment, although with high benefits, involve an investment that makes them unviable in practice.

To optimize the cost of an SDMH, it is evident that the smallest number of signals must be used, without reducing the reliability of the system. This is an issue that is being taken into account in current research. In fact, of the three phases of the development of an SMDH it seems that currently research has focused on the extraction of information from the monitored signals as a basis for optimizing these systems. In this way, being able to obtain more information about the status of the tool with a smaller number of signals reduces system costs.

An order of type KLM-45, pulleys for refineries, is desired to be manufactured, as shown in the plan. The material used is an austenitic stainless steel alloy DIN 1.4418 (X4 Cr Ni Mo 16-5) with a verified Brinell 195 HB hardness. To manufacture it, it is started from alloy ingots that are melted in a crucible and molded.

The cutting conditions for boring are:.

GC4235 Carbide Tool

Tool release angle γTM = 5º

Main position angle χTM = 75°

Advance speed in work fnTM = 0.3 mm/rev.

TTM cutting speed= 30 min.

During the manufacturing of the batch of type KLM-45, the GC4235 carbide tool will suffer progressive wear that can be seen in the surface finishes of the finished pieces. It will not be possible to manufacture the complete batch with a single tool, taking into account that the useful life of the tool will be directly related to the cutting parameters and materials used established in the problem statement.

The modified control chart analyzes the behavior of the process and can predict possible tool failures using statistical methods.

The initial setting of the tool is within the 6σ interval of the normal distribution close to the lower limit of the specification. As the tool wears out, the variability of the process will change, bringing the process closer to the upper limit of the specification.