Manufacturing Process Quality Research Articles

Improving the manufacturing process quality using design of experiments: a case study

Design of experiments (DoE) is a strategy of planning, conducting, analysing and interpreting experiments so that valid conclusions can be drawn efficiently and economically. It has proved to be very effective for improving the process yield, process performance, and process variability. The paper highlights common problems and gaps in the state‐of‐the‐art in DoE. The paper also presents a case study for optimising the product life using DoE methodology. A significant improvement in the product life was observed. The results of the case study were fascinating and would encourage the engineering team within the company to apply this powerful technique in other core processes to achieve process improvement at low costs.

Experimental and numerical residual stress analysis of layer coated composites

Industrial requirements concerning the increased efficiency of modern machine components combined with low material and production cost targets result in the development of new composite materials and material combinations. Especially the application of functional coatings on light metals by thermal spraying can fulfil both requirements. The knowledge of the mechanical and functional properties of the coating is a key requirement for an optimized and repeatable manufacturing process and reproducible high quality composites. These coating properties as well as the lifetime and operation behaviour are mainly influenced by the residual stress situation. This paper describes a new approach to the simulation of the thermal spraying process by modelling a moving heat source in combination with the material transfer and deposition process. The calculated stresses and deformations are consistent with experimental residual stress measurements by means of the advanced hole drilling method. In addition the influence of the residual stresses on the mechanical coating properties is investigated.

Improving the manufacturing process quality and capability using experimental design: A case study

Experimental design is essentially a strategy of planning, designing, conducting and analysing experiments so that valid and reliable conclusions can be drawn in the most effective manner. Experimental design has proved to be very effective for improving the process performance, process capability and reducing rework and replacement costs due to excessive process variability. The paper highlights common problems and gaps in the state-of-the-art in experimental design. The paper also presents a case study performed in a UK firm on a laser welding process for optimizing the product life using experimental design methodology. A significant improvement in the product life was observed. The result of the case study reveals the stimulus for the wider application of experimental design techniques by engineers within the company to achieve process improvement at low costs. Computer softwares such as Minitab and Design-Ease were used for analysing the experimental results.

Predictive control of quality in batch polymerization using hybrid ANN models

AbstractTwo issues involving the methodology used for on‐line control of product quality in batch manufacturing processes are addressed: the generation of fast, data‐driven process models and the use of such process models for on‐line feedback control of product quality. The methodology is investigated using the example of the control of dispersity and molecular weight distribution in a batch reactor for emulsion polymerization of vinyl acetate. An artifical neural network (ANN) is used as a model to predict the quality as a function of the manipulated variables and on‐line measurements. This model is constructed using an augmented dataset that integrates experimental information and knowledge from a mathematical model. The proposed model is compared with other types such as a theoretical model whose key parameters are fitted to experimental data. The hybrid ANN is superior to the parameter‐fitting approach for this case. Experimental and simulation studies confirm the advantage of using the proposed model and the predictive control algorithm.

Energy Levels of Defects in a-Si:H From Optical and Electrical Characteristics

AbstractTwo novel characterization techniques for hydrogenated silicon thin films have been recently proposed which show promise in providing critical feedback for evaluating materials and monitoring the device fabrication process. The first technique is the optical interference spectroscopy for a quick non-destructive measurement of absorption coefficient and refractive index spectra of amorphous- and poly-Si thin films in a wide range of the incident photon energies (0.5–3.5 eV) [1]. By using this technique, the absorption related to defects in the subgap energy region has been determined for device quality thin films. The second technique is the novel version of the field effect conductivity (FEC) method for the direct density-of-states (DOS) determination from analysis of thin film transistor (TFT) quasi-static transfer characteristics [2]. This sensitive, fast, and easy to use, method makes it possible to resolve fine-scale features in the midgap DOS of a-Si:H. In this work, data from two methods of spectroscopy are analyzed together. Very close correlation of results is demonstrated which provides a unique opportunity to identify midgap defect states and to understand the fundamental physics of hydrogenated silicon films. The energy map of defect states in the upper half of a-Si:H bandgap is presented. These results permits to use TFT transfer characteristics and optical interference technique measurements as effective tools to control the quality of TFF manufacturing process.

Predictive control of quality in a batch manufacturing process using artificial neural network models

ADVERTISEMENT RETURN TO ISSUEPREVArticleNEXTPredictive control of quality in a batch manufacturing process using artificial neural network modelsBabu Joseph and Frieda Wang HanrattyCite this: Ind. Eng. Chem. Res. 1993, 32, 9, 1951–1961Publication Date (Print):September 1, 1993Publication History Published online1 May 2002Published inissue 1 September 1993https://doi.org/10.1021/ie00021a019RIGHTS & PERMISSIONSArticle Views626Altmetric-Citations56LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InReddit PDF (2 MB) Get e-Alerts Get e-Alerts

The Use of Computer Simulation in Implementing a Manufacturing Process Quality Modelling System

A manufacturing process quality model for investigating the operation of a manufacturing unit has been developed incorporating the failure mechanism of instantaneous assignable cause, mean drift and standard deviation drift. Describes an illustrative example, showing how the new model can be used in conjunction with simulation to optimize the control of a manufacturing process from a cost‐quality perspective.

Modélisation par éléments finis de la polymérisation de structures composites

ABSTRACT Since the manufacturing process quality conditions both the quality of the structure and the quality of its material constituants, we are going to study the thermochemical phenomena which occur during the polymerization reaction. Therefore, we propose a finite element model for the thermical equations (non-linear, non-stationnary, anisotropic), coupled to the equations of chemical kinetics, in order to include the heat generation during the curing process. To verify the accuracy of this model, the simulation of the curing process of a carbon/epoxy laminated sheet is performed and numerical and experimental results are succesfully compared. Finally, in order to prove that this numerical tool could be an assistance to design and optimization of industrial curing processes, the manufacturing of a complex composite structure is analysed.

Integrating scheduling and control functions in computer integrated manufacturing using artificial intelligence

Proper integration of scheduling and control in Flexible Manufacturing Systems will make available the required level of decision-making capacity to provide a flexibly-automated, efficient, and quality manufacturing process. To achieve this level of integration, the developments in computer technology and sophisticated techniques of artificial intelligence (AI) should be applied to such FMS functions as scheduling. In this paper, we present an Intelligent Scheduling System for FMS under development that makes use of the integration of two AI technologies. These two AI technologies — Neural Networks and Expert Systems — provide the intelligence that the scheduling function requires in order to generate goodschedules within the restrictions imposed by real-time problems. Because the system has the ability to plan ahead and learn, it has a higher probability of success than conventional approaches. The adaptive behavior that will be achieved contribute to the integration of scheduling and control in FMS.

An Integrated Quality Systems Approach to Quality and Productivity Improvement in Continuous Manufacturing Processes

An integrated quality systems methodology is presented as a framework within which the concepts of process control can be used to improve quality and productivity. The process is mathematically described by stochastic time series models which statistically describe how inputs and outputs interact. Several different methods for fault identification, including autocorrelation checks of the model residuals, forecasting prediction intervals, and the cusum chart are compared in terms of relative performance. A helix cable manufacturing process is simulated and analyzed by the methodology and faults are identified and suggestions are made for process improvement. Through the simulation these time series control chart methods are shown to be much more effective than conventional methods such as Shewhart control charts.

The Exponentially Weighted Moving Average

The Shewhart and CUSUM control chart techniques have found wide application in the manufacturing industries. However, workpiece quality has also been greatly enhanced by rapid and precise individual item measurements and by improvements in automatic dynamic machine control. One consequence is a growing similarity in the control problems faced by the workpiece quality control engineer and his compatriot in the continuous process industries. The purpose of this paper is to exposit a control chart technique that may be of value to both manufacturing and continuous process quality control engineers: the exponentially weighted moving average (EWMA) control chart. The EWMA has its origins in the early work of econometricians, and although its use in quality control has been recognized, it remains a largely neglected tool. The EWMA chart is easy to plot, easy to interpret, and its control limits are easy to obtain. Further, the EWMA leads naturally to an empirical dynamic control equation.

Design of an interrelated quality system for a single product manufacturing process with assembly

AbstractThe design of a single product manufacturing system with assembly is considered. The processing is on a lot‐by‐lot basis with the lot size fixed. The decision variables include interrelated single sampling plans, manufacturing process quality levels, incoming raw material quality levels and assembly process quality levels. A solution procedure is given to minimize the expected total of the costs associated with the quality of the finished product subject to a limit on the Average Outgoing Quality Limit of the finished product. An example is provided.

Manufacturing Process Quality Optimization Studies

Manufacturing processes seldom run perfectly. In attempts at improvement, these processes are continually adjusted' by the mechanic, supervisor, and engineer; or more formally, they are studied from manufacturing, quality control, or e..

An Optimal Quality Control Design for a Single-Product Serial Manufacturing System

The design of optimal, interrelated single sampling plans, manufacturing process quality level, and incoming quality level is considered for a single product manufacturing system. Cost components of the system are identified. A mathematical model is dev..

The Use of Cumulative Sums for Sampling Inspection Schemes

In this article Dr Kemp describes the use of the cumulative sum chart for controlling the quality of a continuous manufacturing process. Tables are given from which sampling schemes can easily be devised for controlling a normally distributed variable and the percentage of defective items being produced. A comparison is made between some properties of the cumulative sum chart and those of other types of chart.