A Knowledge-Based Tuning Method for Injection Molding Machines

2000 ◽  
Author(s):  
Dongzhe Yang ◽  
Kourosh Danai ◽  
David Kazmer
Keyword(s):  
Injection Molding ◽  
A Priori ◽  
Statistical Design ◽  
Process Window ◽  
Feasible Region ◽  
Statistical Design Of Experiments ◽  
Tuning Method ◽  
Part Quality ◽  
Knowledge Based ◽  
Experienced Operator

Abstract Complexity of manufacturing processes has hindered methodical specification of machine setpoints for improving productivity. Traditionally in injection molding, the machine setpoints are assigned either by trial and error, based on heuristic knowledge of an experienced operator, or according to an empirical model between the inputs and part quality attributes obtained from statistical design of experiments (DOE). In this paper, a Knowledge-Based Tuning (KBT) Method is presented which takes advantage of the a priori knowledge of the process, in the form of a qualitative model, to reduce the demand for experimentation. The KBT Method is designed to provide an estimate of the process feasible region (process window) as the basis of finding the optimal setpoints, and to update its knowledge-base according to new input-output data that becomes available during tuning. The KBT Method’s utility is demonstrated in production of digital video disks (DVDs).

A Knowledge-Based Tuning Method for Injection Molding Machines

2000 ◽  
Vol 123 (4) ◽  
pp. 682-691 ◽  
Author(s):  
Dongzhe Yang ◽  
Kourosh Danai ◽  
David Kazmer
Keyword(s):  
Injection Molding ◽  
Empirical Model ◽  
A Priori ◽  
Process Window ◽  
Feasible Region ◽  
A Priori Knowledge ◽  
Qualitative Model ◽  
Trial And Error ◽  
Knowledge Based ◽  
Priori Knowledge

Complexity of manufacturing processes has hindered methodical specification of machine setpoints for improving productivity. Traditionally in injection molding, the machine setpoints are assigned either by trial and error, based on heuristic knowledge of an experienced operator, or according to an empirical model between the inputs and part quality attributes, which is obtained from statistical design of experiments (DOE). In this paper, a Knowledge-Based Tuning (KBT) Method is presented which takes advantage of the a priori knowledge of the process, in the form of a qualitative model, to reduce the demand for experimentation. The KBT Method provides an estimate of the process feasible region (process window) as the basis of finding the suitable setpoints, and updates its knowledge-base using the data that become available during tuning. As such, the KBT Method has several advantages over conventional tuning methods: (1) the qualitative model provides a generic form of representation for linear and nonlinear processes alike, therefore, there is no need for selecting the form of the empirical model through trial and error, (2) the use of a priori knowledge eliminates the need for initial trials to construct an empirical model, so an initial feasible region can be identified as the basis of search for the suitable setpoints, and (3) the search within the feasible region leads to a higher fidelity model of this region when the input/output data from consecutive process iterations are used for learning. The KBT Method’s utility is demonstrated in production of digital video disks (DVDs).

Automatic Tuning and Regulation of Injection Molding by the Virtual Search Method

1998 ◽  
Vol 120 (2) ◽  
pp. 323-329 ◽  
Author(s):  
R. Ivester ◽  
K. Danai
Keyword(s):  
Injection Molding ◽  
Statistical Design ◽  
Quality Attributes ◽  
Search Method ◽  
Analytical Models ◽  
Statistical Design Of Experiments ◽  
Input Selection ◽  
Part Quality ◽  
Experienced Operator ◽  
Input Variables

Methodical specification of process inputs for injection molding is hindered by the absence of accurate analytical models. For these processes, the input variables are assigned either by trial and error, based on heuristic knowledge of an experienced operator, or by statistical Design of Experiments (DOE) methods which construct a comprehensive empirical model between the inputs and part quality attributes. In this paper, an iterative method of input selection (tuning) referred to as the Virtual Search Method (VSM) is introduced that conducts most of the search for appropriate machine inputs in a ‘virtual’ environment provided by an approximate input-output (I-O) model. VSM applies the inputs to the process only when it has exhausted the search based on the current I-O model. It evaluates the quality of inputs from the search and updates the I-O model for the next round of search based on measurements of part quality attributes (e.g., size tolerances and surface integrity) after each process iteration. According to this strategy, VSM updates the model only when needed, and thus selectively develops the model as required for tuning the process. This approach has been shown to lead to shorter tuning sessions than required by DOE methods.

Process Window Derivation With an Application to Optical Media Manufacturing

2000 ◽  
Vol 123 (2) ◽  
pp. 303-311 ◽  
Author(s):  
David Kazmer ◽  
Liang Zhu ◽  
David Hatch
Keyword(s):  
Quality Attributes ◽  
Process Models ◽  
Process Window ◽  
Feasible Region ◽  
Part Quality ◽  
Performance Space ◽  
Pareto Optimal Set ◽  
Optical Media ◽  
Quality Specifications ◽  
Optimal Set

This paper derives the process window from quantitative process models. Multi-dimensional clipping algorithms are developed that operate on half-spaces defined from the quality specifications. The resulting polytope is difficult to directly interpret. To support interactive tuning and optimization of manufacturing processes, three types of graphical matrices are presented to the decision maker: (1) the function matrix describes the relations between the process parameters and the manufactured part quality attributes; (2) the process space illustrates the feasible processing space constrained by the product quality specifications; (3) the performance space provides the feasible region of the part quality attributes and the Pareto Optimal set corresponding to the processing space. Optimization of optical media manufacturing is presented to demonstrate the use of the process window to locate a feasible solution and proceed to a desired trade-off of multiple quality attributes.

Tolerance Optimization: A Decomposition Scheme, Variance Reduction and Fractional Approximation

2001 ◽  
Author(s):  
Mohamed H. Gadallah
Keyword(s):  
Variance Reduction ◽  
A Priori ◽  
Statistical Design ◽  
Global Optimum ◽  
Constrained Systems ◽  
Statistical Design Of Experiments ◽  
System Decomposition ◽  
Decomposition Scheme ◽  
Statistical Measures ◽  
Original Objective

Abstract Development of involved optimization algorithms is not an easy task for several reasons: First, every analyst is interested in a specific problem; Second, the capabilities of these methods may not be fully understood a priori; Third, coding of multi-purpose and more involved algorithms is not an easy job. In this paper, the optimization problem employing the near to global optimum algorithm is studied (Gadallah, M.H., 2000). The focus is to exploit 2 ideas: First, the algorithm can be modified to act as a variance reduction technique; Second, the algorithm can be modified to tackle the problem of system decomposition. Both ideas are novel within the context of statistical design of experiments. The first, if fully proved experimentally could yield the simultaneous integration of nominal and variance optimization possible. The second, can be extended to deal with multi-dimensional highly constrained systems with ease. These two ideas are explained wife the use of a simple example to illustrate the idea. An algorithm is developed that deal with the problem in several stages according to a predetermined decomposition scheme. The original objective and constraint functions are dealt with to suit each stage. Accordingly, all NP hard problems can ideally be transformed into NP complete ones with a consequence on the number of stages resulting from decomposition. Several decomposition scenarios are used and their results are compared numerically. Two orthogonal arrays and four composite arrays are used to plan experimentation; these are L27OA and L54OA and their subfamilies. These arrays are compared with respect to their statistical measures. The algorithm as such, is very promising optimization tool, especially for coupling system decomposition and variance reduction. Past work focused on either decomposition or statistical optimization. This work offers both capabilities. Several studies are reviewed and conclusions are drawn.

STATISTICAL DESIGN OF EXPERIMENTS FOR THE Cr(VI) ADSORPTION ON WEED Salvinia cucullata

2013 ◽  
Vol 12 (3) ◽  
pp. 465-474 ◽  
Author(s):  
Saroj Sundar Baral ◽  
Ganesan Surendran ◽  
Namrata Das ◽  
Polisetty Venkateswara Rao
Keyword(s):  
Design Of Experiments ◽  
Statistical Design ◽  
Statistical Design Of Experiments

scholarly journals High-Order Filtered PID Controller Tuning Based on Magnitude Optimum

Mathematics ◽  
2021 ◽  
Vol 9 (12) ◽  
pp. 1340
Author(s):  
Damir Vrančić ◽  
Mikuláš Huba
Keyword(s):  
A Priori ◽  
Higher Order ◽  
Process Models ◽  
Pid Controllers ◽  
Tuning Method ◽  
Output Noise ◽  
Pid Controller Tuning ◽  
Output Time ◽  
Tuning Methods ◽  
Measured Input

The paper presents a tuning method for PID controllers with higher-order derivatives and higher-order controller filters (HO-PID), where the controller and filter orders can be arbitrarily chosen by the user. The controller and filter parameters are tuned according to the magnitude optimum criteria and the specified noise gain of the controller. The advantages of the proposed approach are twofold. First, all parameters can be obtained from the process transfer function or from the measured input and output time responses of the process as the steady-state changes. Second, the a priori defined controller noise gain limits the amount of HO-PID output noise. Therefore, the method can be successfully applied in practice. The work shows that the HO-PID controllers can significantly improve the control performance of various process models compared to the standard PID controllers. Of course, the increased efficiency is limited by the selected noise gain. The proposed tuning method is illustrated on several process models and compared with two other tuning methods for higher-order controllers.

scholarly journals Synthesis of an Addition-Crosslinkable, Silicon-Modified Polyolefin via Reactive Extrusion Monitored by In-Line Raman Spectroscopy

Polymers ◽  
2021 ◽  
Vol 13 (8) ◽  
pp. 1246
Author(s):  
Steffen Ulitzsch ◽  
Tim Bäuerle ◽  
Mona Stefanakis ◽  
Marc Brecht ◽  
Thomas Chassé ◽  
...  
Keyword(s):  
Raman Spectroscopy ◽  
High Performance ◽  
Process Analytical Technology ◽  
Statistical Design ◽  
Reactive Extrusion ◽  
Statistical Design Of Experiments ◽  
Grafting Efficiency ◽  
Grafting Reaction ◽  
Central Composite Experimental Design ◽  
Process Factors

We present the modification of ethylene-propylene rubber (EPM) with vinyltetra-methydisiloxane (VTMDS) via reactive extrusion to create a new silicone-based material with the potential for high-performance applications in the automotive, industrial and biomedical sectors. The radical-initiated modification is achieved with a peroxide catalyst starting the grafting reaction. The preparation process of the VTMDS-grafted EPM was systematically investigated using process analytical technology (in-line Raman spectroscopy) and the statistical design of experiments (DoE). By applying an orthogonal factorial array based on a face-centered central composite experimental design, the identification, quantification and mathematical modeling of the effects of the process factors on the grafting result were undertaken. Based on response surface models, process windows were defined that yield high grafting degrees and good grafting efficiency in terms of grafting agent utilization. To control the grafting process in terms of grafting degree and grafting efficiency, the chemical changes taking place during the modification procedure in the extruder were observed in real-time using a spectroscopic in-line Raman probe which was directly inserted into the extruder. Successful grafting of the EPM was validated in the final product by 1H-NMR and FTIR spectroscopy.

scholarly journals Evaluation of Cutting-Tool Coating on the Surface Roughness and Hole Dimensional Tolerances during Drilling of Al6061-T651 Alloy

Materials ◽  
2021 ◽  
Vol 14 (7) ◽  
pp. 1783
Author(s):  
Hamza A. Al-Tameemi ◽  
Thamir Al-Dulaimi ◽  
Michael Oluwatobiloba Awe ◽  
Shubham Sharma ◽  
Danil Yurievich Pimenov ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Cutting Tool ◽  
Good Practice ◽  
Cutting Tools ◽  
Statistical Design ◽  
Cutting Parameters ◽  
Statistical Design Of Experiments ◽  
Hole Quality ◽  
Coated Tools ◽  
Tool Coating

Aluminum alloys are soft and have low melting temperatures; therefore, machining them often results in cut material fusing to the cutting tool due to heat and friction, and thus lowering the hole quality. A good practice is to use coated cutting tools to overcome such issues and maintain good hole quality. Therefore, the current study investigates the effect of cutting parameters (spindle speed and feed rate) and three types of cutting-tool coating (TiN/TiAlN, TiAlN, and TiN) on the surface finish, form, and dimensional tolerances of holes drilled in Al6061-T651 alloy. The study employed statistical design of experiments and ANOVA (analysis of variance) to evaluate the contribution of each of the input parameters on the measured hole-quality outputs (surface-roughness metrics Ra and Rz, hole size, circularity, perpendicularity, and cylindricity). The highest surface roughness occurred when using TiN-coated tools. All holes in this study were oversized regardless of the tool coating or cutting parameters used. TiN tools, which have a lower coating hardness, gave lower hole circularity at the entry and higher cylindricity, while TiN/TiAlN and TiAlN seemed to be more effective in reducing hole particularity when drilling at higher spindle speeds. Finally, optical microscopes revealed that a built-up edge and adhesions were most likely to form on TiN-coated tools due to TiN’s chemical affinity and low oxidation temperature compared to the TiN/TiAlN and TiAlN coatings.

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