Online product quality monitoring through in-process measurement

Gao, Robert X.; Tang, Xinyao; Gordon, Guthrie; Kazmer, David O.

doi:10.1016/j.cirp.2014.03.041

Cited by 64 publications

(36 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This development is partially motivated by the desire to improve quality. Unambiguously, quality is a significant indication that has a substantial impact on productivity and economy of manufacture, particularly in the field of mass production [2]. Direct measurement of the product compositions of the distillation column is a crucial issue.…”

Section: Introductionmentioning

confidence: 99%

Hybrid Intelligent Approach for Predicting Product Compositions of a Distillation Column

Al-Dunainawi¹,

Abbod²

2016

ijarai

View full text Add to dashboard Cite

Abstract-Compositions measurement is a vitally critical issue for the modelling and control of distillation process. The product compositions of distillation columns are traditionally measured using indirect techniques via inferring tray compositions from its temperature or by using an online analyser. These techniques were reported as inefficient and relatively slow methods. In this paper, an alternative procedure is presented to predict the compositions of a binary distillation column. Particle swarm optimisation based artificial neural network PSO-ANN is trained by different algorithms and tested by new unseen data to check the generality of the proposed method. Particle swarm optimisation is utilised, here, to choose the optimal topology of the network. The simulation results have indicated a reasonable accuracy of prediction with a minimal error between the predicted and simulated data of the column.

show abstract

Section: Introductionmentioning

confidence: 99%

Hybrid Intelligent Approach for Predicting Product Compositions of a Distillation Column

Al-Dunainawi¹,

Abbod²

2016

ijarai

View full text Add to dashboard Cite

show abstract

“…Traditionally, quality control is performed offline, after a part is produced (Gao et al, 2014), and the Geoform device was designed for this kind of measurement. It is based on the complete automatic set, where the detail is placed manually (Fig.…”

Section: Out-of-roundness Measurement With the Air Gagesmentioning

confidence: 99%

Dynamics of the Non-Contact Roundness Measurement with Air Gages

Jermak

Rucki

2016

Acta Mechanica Et Automatica

View full text Add to dashboard Cite

The paper presents the results of investigations on the air gages dynamic characteristics in the measurement of the round profiles of motor cylinders. The principle of the measuring device is explained, and the analysis of the air gages dynamics is described. The results of dynamic calibration enabled to eliminate those configurations of air gages that may not meet the requirements of the measurement they were designed for. After the proper air gages were chosen, the entire system underwent the accuracy test and passed it successfully revealing the method accuracy better than 10% compared to the reference measurement.

show abstract

“…Friesenbichler has showed that the viscosity measured by a capillary rheometer differs by 10% from the value determined during injection molding . In‐line measurements, in addition to determining the material rheological characteristics under processing conditions, allow process control and its optimization …”

Section: Introductionmentioning

confidence: 99%

The Influence of Processing Conditions on the Polypropylene Apparent Viscosity Measured Directly in the Mold Cavity

Sykutera

Wajer

Kościuszko

et al. 2018

Macromolecular Symposia

View full text Add to dashboard Cite

Measurements of rheological properties of polymeric materials play an increasingly important role in the polymer plastics industry. Knowledge about the plasticized material flow behavior is essential at the injection molds design stage. The polymeric viscosity curves usually are determined by a capillary rheometer tests. Nevertheless, the rheological properties determined this way differ from those observed during actual processing conditions. This paper presents a comparison of apparent viscosity measurements of polypropylene conducted by three methods. The first one was plastometer measurements made at different masses of test load. The second method evaluated the viscosity in the injection mold cavity equipped with pressure and temperature sensors. Capillary rheometer was used as the third method. It was observed that polypropylene viscosity curves, determined by different methods have a similar pattern. Comparing changes in apparent viscosity values obtained with the capillary rheometer and directly in the mold cavity, the largest differences were found for the shear rate below 1000 s −1. This proves the non‐isothermal measurement in the injection mold cavity. In the range of shear rate above 1000 s−1, the apparent viscosity determined directly in the injection mold was about 40 Pa · s greater than that measured by the rheometer, regardless of the test temperature. The results recorded by the plastometer reflect the real polypropylene viscosity curve at low shear rate values in a better way.

show abstract

Online product quality monitoring through in-process measurement

Cited by 64 publications

References 10 publications

Hybrid Intelligent Approach for Predicting Product Compositions of a Distillation Column

Hybrid Intelligent Approach for Predicting Product Compositions of a Distillation Column

Dynamics of the Non-Contact Roundness Measurement with Air Gages

The Influence of Processing Conditions on the Polypropylene Apparent Viscosity Measured Directly in the Mold Cavity

Contact Info

Product

Resources

About