CN111907025B

CN111907025B - Method and system for optimizing the course of movement of a molding machine assembly or handling device

Info

Publication number: CN111907025B
Application number: CN202010368630.XA
Authority: CN
Inventors: M·奥伯赫伯; F·J·基利安
Original assignee: Engel Austria GmbH
Current assignee: Engel Austria GmbH
Priority date: 2019-05-07
Filing date: 2020-04-28
Publication date: 2022-02-08
Anticipated expiration: 2040-04-28
Also published as: AT522075A4; DE102020109950A1; AT522075B1; CN111907025A

Abstract

The invention relates to a method for optimizing the course of movement of a handling device assigned to a moulding machine and of at least one selected component of the moulding machine, said optimization being carried out with respect to the entire system comprising said handling device and said at least one selected component of the moulding machine, and at least the following steps being provided: defining at least one limit on the course of motion of the handling apparatus and/or the course of motion of the at least one selected component of the forming machine; providing at least one quality function, wherein the at least one quality function provided relates to only one of the motion processes and represents the entire system by relating to limits for the entire system, or the at least one quality function provided relates to the entire system; calculating a resulting trajectory for the course of motion of the at least one selected component of the handling apparatus and the forming machine by limiting the mass function taking into account the at least one limit.

Description

Method and system for optimizing the course of movement of a molding machine assembly or handling device

Technical Field

The present invention relates to a method and system for optimizing the course of movement of a molding machine assembly or handling device.

Background

DE 102006037976B 4 describes a method for synchronizing the movement of a handling device assigned to a molding machine with the movement of at least one selected component of the molding machine. This results in a reduction in cycle time to some extent. The method is limited to selected components of the molding machine in the form of mold clamping plates and to a reduction in cycle time.

Disclosure of Invention

The object of the present invention is to provide a method of the same type and a system configured for implementing said method, in which method it is possible to choose what mass function (britefunktional) should be referred to for optimization and which method can be used more generally in relation to selected components of the forming machine.

The object is solved by a method and a system. According to a first parallel aspect of the invention, the method is used for optimizing a course of motion with at least one movement to be carried out of a handling device assigned to a molding machine and a course of motion with at least one movement to be carried out of at least one selected component of the molding machine, characterized in that the optimization is carried out with respect to the entire system comprising the handling device and the at least one selected component of the molding machine, and in that at least the following steps are provided: defining at least one, preferably geometrical and/or kinematic and/or dynamic, limit with respect to the course of motion of the handling apparatus and/or of the at least one selected component of the forming machine; providing at least one mass function, wherein the at least one mass function provided relates to only one of the motion processes and represents the entire system by relating to limits for the entire system including the at least one selected component of the handling apparatus and the molding machine, or the at least one mass function provided relates to the entire system including the at least one selected component of the handling apparatus and the molding machine; calculating a resulting trajectory for the course of motion of the handling apparatus and the course of motion of the at least one selected component of the molding machine by limiting the mass function taking into account the at least one limit. According to a second embodiment of the invention, the method is used for optimizing a movement sequence with at least one movement to be carried out of a handling device assigned to a molding machine or a movement sequence with at least one movement to be carried out of at least one selected component of the molding machine in the presence of corresponding further movement sequences, characterized in that the method comprises at least the following steps: providing a trajectory that references the respective other course of motion; defining at least one, preferably geometrical and/or kinematic and/or dynamic, limit with respect to the course of motion of the handling apparatus and/or of the at least one selected component of the forming machine; providing at least one mass function, wherein the at least one mass function provided relates to only one of the motion processes and represents the entire system by relating to limits for the entire system including the at least one selected component of the handling apparatus and the molding machine, or the at least one mass function provided relates to the entire system including the at least one selected component of the handling apparatus and the molding machine; calculating a resulting trajectory for the course of motion of the handling apparatus and the course of motion of the at least one selected component of the molding machine by limiting the mass function taking into account the at least one limit. The system according to the invention, comprising a molding machine, preferably a plastic injection molding machine, and a handling device, preferably an arm or a gripper of a handling device, is characterized in that a control device of the molding machine or of the handling device or a common control device of the molding machine and the handling device is configured for carrying out the method according to the invention or is connected via a data remote connection to a control device for carrying out the method according to the invention.

The basic idea of the invention is to synchronize the trajectory of the movement sequence of the handling device with the trajectory of the movement sequence of at least one selected component of the molding machine in an optimized manner with reference to the quality function, that is to say not to optimize each movement sequence itself, but rather to optimize the entire system taking into account the two movement sequences to be optimized. In this way, dead times and waiting times during the respective movements can be avoided.

The entire system is taken into account by a mass function which relates to the entire system or by a mass function which relates to only one of the two motion processes to be optimized. In the latter case, the reference to the entire system is made by the influence of other motion processes on the limit to be selected.

Not only the starting point of the respective movement process but also the trajectory of the respective movement process (i.e. from the starting point to the end point together with the path traveled by the points lying between these points as a whole) is ascertained (i.e. ascertained or calculated)

Instead of the starting point, a starting range can be defined, i.e. the speed and position can be varied in some way, but are (not previously) known. The starting point itself may be an optimization variable. The termination point is preferably defined in a coordinate system fixed with respect to the mold (also referred to as "model") and may have variable position and velocity with respect to space.

The set of starting parameters may be from a previously optimized trajectory or a measured trajectory during a work cycle.

For the optimization, geometric and/or kinematic and/or dynamic and/or process-technical limitations with respect to the course of motion of the handling device and/or the course of motion of the at least one selected component of the molding machine need to be defined.

The calculation of the course of motion of the handling device and/or of the trajectory resulting from the course of motion of the at least one selected component of the molding machine can be carried out in a manner known per se by limiting the mass function taking into account the limits.

The handling device may be designed, for example, in the form of a handling device (robot), wherein a holder that is movable relative to the handling device may be arranged at a termination point (TCP point mold center point) of the handling device.

Optimization of the overall system including the clamp, the handling device (e.g., the handling device configured to the molding machine), and the mold of the molding machine (e.g., the at least one selected component of the molding machine) will be discussed as an example.

The example includes the steps of:

providing a mathematical model for two multi-body systems (operating device and clamp on the one hand and moulding machine with mould on the other hand)

-determining limits (constraints), such as:

■ minimum distance between operating equipment and clamp and die

■ maintain the minimum distance even in the event of an emergency stop

-confirming start conditions/boundary conditions

-selecting a common quality function for the handling equipment, the gripper and the mould, for example with reference to:

■ cycle time, particularly extended time for extraction by handling equipment and fixtures

■ energy requirement for movement

Parameterization of the trajectory (point-to-point optimization) as a function of the trajectory parameters

-carrying out optimization online or offline by solving an optimization problem or alternatively by iteratively adapting a motion process based on simulation data or measurement data

If the course of movement of a selected component of the handling device or of the molding machine has been confirmed, an optimized adaptation of the other course of movement can be carried out by means of the invention when one of the courses of movement changes. For this purpose, the trajectory is provided with reference to the modified course of motion.

The constraints on the two movement processes, which are predefined by the molding machine (including hardware or safety), must be taken into account. Additionally, the (course-dependent) limits that are variable for one or both courses of motion may be input by the operator.

The quality function may be provided with reference to the entire system including the handling apparatus and the at least one selected component of the molding machine.

Calculating trajectories derived for other motions by limiting the mass function under consideration of the constraints.

An example for a limitation is a (e.g. dynamic) interference profile

And/or the location that must be reached at a particular time. The limit may be considered in the form of a penalty term (Straftermen) in the quality function.

The quality function may relate to the entire cycle time of the working cycle of the molding machine or a fraction of the entire cycle time of the molding machine. Alternatively or additionally, the mass function may relate to the energy requirements for both movements. This may depend on the electrical architecture of the whole system (e.g. the efficiency of the feedback unit in relation to the operating point).

The molding machine is preferably a plastic injection molding machine.

The handling device is preferably an operating device with one arm or a plurality of arms and optionally a gripper.

The optimization can be carried out in a single step in such a way that the optimization problem is solved by the optimization tool. Alternatively, the optimization can be carried out iteratively in such a way that first a first movement process of the handling device and/or the molding machine is carried out and the resulting mass function for the one or more movement processes is calculated and subsequently the modification of the one or more movement processes is carried out in such a way that the resulting mass function for the modified one or more movement processes is greater or smaller (depending on the optimization problem). This is performed until no significant change in the quality function is obtained anymore. The iterative adaptation can be carried out both on the basis of actual measurement data and with the aid of simulation results. Example (b):

as an example, it is cited that a part molded in a mold part of a mold of a molding machine is taken out by a jig provided on a TCP of an operating device, wherein the mold part is provided on a movable mold clamping plate of the molding machine:

-providing a partitioning of the optimization problem:

■ trajectories of handling equipment and grippers to take-out point (move-in and eject) and mold part opening trajectory and mold ejection trajectory

■ trajectory of the handling device and the gripper from the removal point (removal) and, if necessary, the closing trajectory of the mould parts

-initial case of optimization:

■ the trajectory of the handling device and the gripper is part of the optimization and is not predefined (only boundary conditions, such as start and end points or start or end areas are predefined)

■ the kinetic models of the handling equipment, the clamps and the forming machine are known (possibly even elastic models containing elastic movements in addition to rigid movements):

■ where vector s represents the position of the handling device, clamp and machine, vector v represents the speed of the handling device, clamp and machine, mass matrix M represents the mass of the handling device, clamp and machine, vector F represents the input force (e.g. system input or motor torque), and vector G represents other dynamic (disturbance) effects.

■ maximum torque, acceleration, speed of the operating device and clamp are known (also known for emergency stop situations)

■ the maximum torque, acceleration, speed, etc. of the molding machine is known (also for emergency stop situations)

■ the current actual values of the molding machine may be known

-formulating an optimization problem for calculating an optimized trajectory:

the above condition can be formulated as an optimization problem as follows:

consider that:

g(x(t_e))＝0

h(x(t)，u(t))≤0

the quality function J to be minimized, also commonly referred to as the Bolza quality function, includes a function of the final state (the meier term M (x (t)_e) Not to be confused with the quality matrix) and an integration part (lagrange terms L (x (t), u (t)). The latter can be a function of the control variable/optimization variable u (t) as well as of the system state x (t). t is t_eIs the trajectory duration.

The constraints and restrictions can be in the form of a dynamic system

u (t)) as the equality condition g (x (t))_e) 0 or in the inequality condition h (x (t), u (t) ≦ 0.

-a process for calculating an optimized trajectory:

■ formulating a problem description

■ define optimization variables

■ define limits

■ providing a quality function

Problem description:

-trajectory to the take-out point:

■ identifying a starting point or starting area (no moment), the operating equipment and the clamp being outside the closed area (i.e. the movement area) of the machine

■ identify the point of withdrawal or region of withdrawal. There are different possibilities here, for example:

■ fixed position, fixed speed, fixed time

■ range of position, speed, and time

■ the trajectory of the movable die clamping plate is variable but known a priori in time → synchronizing the trajectory of the handling device and the clamp with the trajectory of the movable die clamping plate

■ the trajectory of the movable die clamping plate is variable but known in real time → synchronizing the trajectory of the handling device and the clamp with the trajectory of the movable die clamping plate

■ identify the contact points of the handling equipment and the clamp with the receiving head or mold assembly of the molding machine.

There are different possibilities here, for example:

■, the fixed or calculable position being changeable with respect to the moment of release (by moving the movable die-clamping plate)

■ the point of contact as a function of position and time is known in advance by moving the movable mold clamping plates

■ the point of contact as a function of position and time is known in real time by moving the movable mold clamping plates

-trajectory from the take-off point:

■ identifying an end point (fixed position of the gripper, no moment) or end zone, the operating device and the gripper being outside the closed zone of the molding machine

■ identify the point of withdrawal or termination area. There are different possibilities here, for example:

■ fixed position, fixed speed, fixed and known time

■ location range, speed range, time range (time period)

■ the position is variable but known a priori in time, the speed is variable but known a priori in time, the time is fixed and known

■ position variable and partially optimized (or equivalently: difference in absolute position of the clamp and the handling device relative to the movable die clamping plate)

Optimizing variables:

version 1 a:

■ the temporal and geometric curves of the trajectory of the operating device and the gripper are determined by optimization.

■ the theoretical trajectories of the movable mold clamping plates and ejectors of a molding machine are known in advance.

■ the point of removal is known in time and location. There is no adaptation of the take-out point to the actual trajectory.

■ assume that: the former ideally follows its trajectory.

■ the starting and ending points or areas of interest of the handling equipment and the jig are fixed.

Version 1 b:

■ the time and geometrical profile of the trajectory of the gripper and the operating device is determined by optimization.

■ calculates the ideal (calculated according to the electromechanical model) actual trajectory of the movable mold clamping plate and ejector of the molding machine.

■ the point of removal is known in time and location. There is no adaptation of the take-out point to the actual track.

■ assume that: the molding machine follows its trajectory with the calculated physical behavior so that the calculated actual trajectory coincides well with the actual trajectory.

-version 1 c:

■ appended to version 1a and/or 1b

■ if no changes affecting the mold motion are implemented, the optimization results from the previous cycle may be used. This process can also be performed in versions 2 to 5 discussed below.

-version 2:

■ the trajectories of the movable mold clamping plates and ejector of the molding machine are known in advance (always the same).

■ the point of extraction is determined by optimization in time and in location. At the removal point, the gripper and the handling device are motion-synchronized in the sense that they have the same speed as the movable mold platen.

■ assume that: the former ideally follows its trajectory.

■ the starting and ending points or areas of interest of the jig and handling equipment are fixed.

-version 3:

■ the trajectories of the movable mold clamping plates and ejectors of the molding machine are not known a priori and the motion control of the clamps and the operating equipment are known in real time.

■ the point of extraction is determined by optimization in time and in location. At the removal point, the gripper and the handling device are (real-time) movement synchronized in the sense that they have the same speed as the movable mold clamping plate.

-version 4:

■ the time profile of the trajectory of the movable mold clamping plate and ejector of the molding machine is determined by optimization.

-version 5:

With the additional conditions:

no collision between the gripper, the operating device and the forming machine:

■ do not encroach on the working space of the handling equipment, jigs and forming machines, which is variable in time.

■ do not violate the operating equipment and the time-variable working space of the molding machine in the event of an emergency stop of the molding machine and/or the operating equipment.

Kinematic limits of the molding machine and of the operating equipment and of the clamps are not allowed to be exceeded.

The limit values of dynamics of the (non-linear) forming machine and operating equipment and the clamps are not allowed to be exceeded.

- (the extraction point can also be variably) defined:

■ time of day or duration

■ moulding machine, at least approximately equal moments in time of absolute position of ejector, operating device and gripper of the moulds

■ the difference between the speed of the mold of the molding machine and the speed of the clamp and the operating device does not exceed a predetermined level

-opening stroke > ejection stroke

The maximum vibration or bending moment in the operating device is not allowed to be exceeded.

Quality function (different possibilities):

-time optimization:

■ minimizing the extension of the removal time by intervening the operating device and the clamp as compared to the opening time without intervening the operating device and the clamp.

■ events may include elastic models that are computed together and input into the optimization in order to minimize the oscillation of the overall system and therefore the oscillation duration.

-energy optimization

Stability with respect to vibrations of the operating device (tracking, dynamics, friction, collision, etc.)

Heat release in electrical components (switchgear, regulator … …)

Optimization of peak load on the operating equipment and/or the molding machine

Weighting of different criteria (time, energy, peak, etc.)

Process stability with respect to different criteria, for example, total cycle time.

Alternatively or additionally, the placing of the inlays into the molds (as selected components of the molding machine) of the molding machine may be handled in a similar manner by the handling apparatus and the grippers (as configured to the handling apparatus of the molding machine).

For the purposes of the present invention, a molded part or the like (for example a sprue) produced is to be understood as a component of a molding machine, as long as the component of the molding machine is located in the region of the molding machine, in particular is kinematically coupled thereto.

Alternatively or additionally, the removal of the pouring opening can be handled in a similar manner by means of handling devices and clamps (as the handling devices assigned to the molding machine).

In the molding machine according to the invention, the implementation of the optimization can be carried out by the operator as follows:

the selection of the optimization variables of variants 1 to 5 discussed above can be carried out expediently, for example, in a combo list box (drop-down menu) and/or in an intuitive symbol diagram.

The selection of the quality function can also be made conveniently.

The starting position of the operating device can be taught (or advantageously also optimized).

The extreme positions of the forming machine and the operating equipment can be taught (or automatically ascertained):

■ Molding machine mold area open

■ the gripper of the handling device is moved into the moulding machine into a minimum position so that the moulding machine can be closed as far as possible

■ shaping machine closed until it is about to collide with the clamp

■ the clamp is removed from the molding machine so that the molding machine can be closed.

-a removal position

■ the removal position of the operating device can be taught (or advantageously optimized as well).

■ may be fixed in position, velocity, acceleration in a fixed-shape coordinate system.

■ can be ascertained automatically by means of an external sensor device, for example a camera system or a locating device with an RFID or NFS system.

For example, the following quality functions can be provided for specific applications:

consider that:

x(t_e)＝x_e

F_min≤F≤F_max

v≤v_max

the Meier term is selected here, for example, as M (x (t)_e) 0). Using a weighting factor k₁And k₂Weighting is performed between time optimization and energy optimization. Special cases k₁1 and k ₂0 provides a time-optimized solution. t is t_eIs the trajectory duration. The first additional condition describes the dynamical system with states s (position) and v (velocity). M denotes the mass matrix and the G (s, v) term contains all the remaining possibly non-linear terms, such as friction or gravity terms. The initial state of the system is s (t is 0) s₀And a speed v (t-0) v₀In the form of the initial conditions. By equalising condition x (t)_e)＝x_eTogether with x_e＝[s_e v_e]^TTo require the attainment of a defined final state.

The manipulated variable limit and the state limit can be considered in the form of an inequality condition (F)_min≤F≤F_max，v≤v_max)。

The advantages of the optimization as a whole will be clarified by the following exemplary signal trends.

Drawings

Fig. 1a shows a comparison of a standard loop with a time-optimized solution according to the prior art.

Fig. 1b shows the overall energy consumption E of the robot and the mould movement.

Figure 2a shows the reduction in extraction time.

Fig. 2b shows the minimization of the energy consumption.

Detailed Description

Fig. 1a shows a comparison of a standard cycle versus time optimized solution according to the prior art:

once model (q)_F) To final position (thin line, track duration t)_e1) The robot starts to move (q)₁And q is₂) Machine with time-optimized solutionThe person obtains an early start signal and interacts with the mold as soon as possible (bold line, track duration t)_e2) Synchronization, in which the cycle time Δ t can be clearly seen_eIs reduced. Furthermore, the overall energy consumption E (see FIG. 1b) of the robot and mold movements is shown (time optimized: bold line, not optimized: thin line).

In the time-optimized trajectory planning of the individual components, each component itself moves as fast as possible. It has been shown that the optimization of a single movement does not necessarily lead to an optimization of the entire system, which on the one hand may lead to unnecessary stopping times of the individual components and on the other hand may lead to an avoidable high energy consumption.

However, it is possible by overall consideration to reduce the removal time to the minimum technically possible value and at the same time to minimize the energy consumption (see fig. 2a and 2 b).

As shown in fig. 2a, a mold q_FAt time t_Fe1Reach the final position and therefore compare the robot (q)₁And q is₂) Faster and has to wait there (thin line). Although the path duration of the mold increases to t by an overall optimization (bold line)_Fe2However, this has no effect on the total duration of the withdrawal. Energy savings are obtained by reduced die dynamics (see lower bold lines in fig. 2 b).

The calculation of the optimization can be carried out in a local control of the molding machine and/or of the operating device or remotely via a data connection in a remote computer.

Preferably, the calculated optimized trajectory is part of a partial data set for a particular molding machine and a particular selected component of the molding machine.

Claims

1. Method for optimizing a course of motion with at least one movement to be carried out of a handling device assigned to a molding machine and a course of motion with at least one movement to be carried out of at least one selected component of the molding machine, characterized in that the optimization is carried out with respect to the entire system comprising the handling device and the at least one selected component of the molding machine, and in that at least the following steps are provided:

-defining at least one limit on the course of motion of the handling device and/or of the at least one selected component of the forming machine;

-providing at least one mass function, wherein the at least one mass function provided relates to only one of the motion processes and represents the entire system by relating to limits for the entire system including the at least one selected component of the handling apparatus and the molding machine, or the at least one mass function provided relates to the entire system including the at least one selected component of the handling apparatus and the molding machine;

-calculating a resulting trajectory for the course of motion of the handling apparatus and the course of motion of the at least one selected component of the molding machine by limiting the mass function taking into account the at least one limit.

2. Method for optimizing a movement sequence with at least one movement to be carried out of a handling device assigned to a molding machine or of at least one selected component of a molding machine with at least one movement to be carried out in the presence of respective further movement sequences, characterized in that the method has at least the following steps:

-providing a trajectory with reference to respective other motion processes;

3. Method according to claim 1 or 2, characterized in that the interference profile and/or at least one position that has to be reached at a specific time is provided as a limit.

4. Method according to claim 1 or 2, characterized in that the quality function relates to the entire cycle time of the molding machine or a fraction of the entire cycle time of the molding machine.

5. A method according to claim 1 or 2, characterized in that the quality function relates to:

-energy requirements of both motion processes;

-minimizing the extension of the extraction time by intervening on the handling apparatus compared to the opening time of the moulding machine without intervening on the handling apparatus;

-stability with respect to vibrations of the handling device;

-heat release in the electrical components of the handling equipment and/or the moulding machine.

6. A method according to claim 1 or 2, characterized by calculating elastic models of the handling equipment and/or the moulding machine together in order to reduce vibrations of the entire system.

7. Method according to claim 1 or 2, characterized in that for at least one of the courses of motion a variable limit is predefined by an operator.

8. Method according to claim 1 or 2, wherein said constraint is a geometric and/or kinematic and/or kinetic constraint.

9. System comprising a moulding machine and a handling device, characterized in that a control device of the moulding machine or of the handling device or a common control device of the moulding machine and the handling device is configured for carrying out a method according to any one of claims 1 to 8 or is connected via a data remote connection with a control device for carrying out a method according to any one of claims 1 to 8.

10. The system of claim 9, wherein the molding machine is a plastic injection molding machine.

11. System according to claim 9 or 10, characterized in that the handling device has an arm or a gripper.