The Design of Experiments as a Methodological Framework for the Improvement of Manufacturing Processes

Industries seek changes in manufacturing processes by designing or redesigning them, to improve the quality of products, reduce costs and cycle times, change materials, modify methods, design innovative products, among others. Facing these demands requires a powerful methodological framework known as Design of Experiments. Most of literature focuses on the application of these techniques in the areas of statistics and quality. However, the variety of problems facing engineers in industry is wide and includes different levels of complexity, ranging from the design of new products, improvement of design, maintenance, control and improvement of manufacturing processes, maintenance and repair of products, among others. This chapter provides the reader different applications of this methodology in industry, to highlight the importance and benefits of knowing and applying these techniques. It will present the application of this methodology in a general way and finally, it will discuss different case studies that use this methodology in industry.

Design of Experiments in an Electrochemical Process

This chapter applies design of experiments to improve plating performance and better practices in an electrochemical process within a company making electronic components. Specifically, the electroplated process of a metal housing served as the object of study. This process consists of plating an aluminum housing with silver (Ag) to improve the electrical signal characteristics and properties. It includes multiple factors affecting the process, which are clearly seen in the diverse failures such as electric response, pollution by solid waste, among others. These directly impact production costs and delivery time. To minimize the mentioned failures, diverse critical factors were enlisted discovering that the principal problem is the homogeneous distribution of the final finish of the commented product. Particularly, the final finish is realized with silver so it directly affects the electric response as final quality test.

Design of Experiments in Engineering Education

The chapter will start with an overview of today´s challenges of engineering education. DOE can be very effective for solving problems in view of the new pedagogical challenges in engineering education. The chapter reviews the progress of DOE in engineering teaching and learning for problem solving and for product/process optimization with focus on engineering education in this new millennium. The goal is to identify the main engineering areas accounting for the use of statistical experimental design in engineering education as well as the main teaching/learning strategies and the combination of other tools used to support the use of DOE in engineering education. The main contribution will be to bring up ideas from studies of DOE in teaching/learning engineering environments to better understand the deficit of utilization of such type of approaches in academic projects/experiments despite the common utilization of DOE in statistics and quality literature.

Optimizing the Size of Drug-Loaded Nanoparticles Using Design of Experiments

Nanoparticles formed from lipids are currently applied successfully to deliver drugs. The particle size of the nanoparticle system is an essential characteristic to enhance the entrance of the drugs inside tissues and cells. Using design of experiment is appealing to find the specific conditions to optimize particle size of drug-loaded nanoparticles. Authors of this chapter applied a fractional factorial design of half fraction 24-1 with levels between continue factors, finding statistically significant differences for two factors such as concentrations of drugs and type of solvent where the organic phase is dissolved. This design shows the optimization of a formulation of capsaicin in solid lipid nanoparticles. The chapter also includes information on methods to prepare solid lipid nanoparticles (SLN), the variables involved, and a selection of studies about optimization of SLN formulations.

The Role of Multivariant Analysis on the Interpretation of FTIR and Raman Spectra

FTIR and Raman spectroscopy are complementary spectroscopic techniques that play an important role in the analysis of molecular structure and the determination of characteristic vibrational bands. Vibrational spectroscopy has a wide range of applications including mainly in physics and biology. Its applications have gained tremendous speed in the field of biological macromolecules and biological systems, such as tissue, blood, and cells. However, the vibrational spectra obtained from the biological systems contain a large number of data and information that make the interpretation difficult. To facilitate the analysis, multivariant analysis comprising the reduction of the dimension of spectrum data and classification of them by eliminating redundancy data, which are obtained from the spectra and does not have any role, becomes critical. In this chapter, the applications of Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), and their combination PCA-LDA, which are widely used among multivariant techniques on biological systems will be disclosed.

Application of Design of Experiments in Biofuel Production

Biofuels emerge as an alternative to mitigate climate change. In this sense, four biofuels generations have been proposed to produce clean and renewable fuels. To achieve this, the development of these fuels requires an extensive and rigorous experimental work that will bring optimal results in short time periods. Hence, to accelerate the development of clean fuels, the Design of Experiments (DoE) methodologies are a useful tool to improve the operational conditions such as temperature, time, pressure, and molar ratios. Several authors have studied and optimized the different biofuel production systems using Factorial Designs and Response Surface Design methods and statistical analysis with reliable results. This chapter reviews and classifies the results obtained by these investigations and demonstrates the scopes and limitations of the application of DoE.

Application of the Simultaneous Perturbation Stochastic Approximation Algorithm for Process Optimization

There are different techniques for the optimization of industrial processes that are widely used in industry, such as experimental design or surface response methodology to name a few. There are also alternative techniques for optimization, like the Simultaneous Perturbation Stochastic Approaches (SPSA) algorithm. This chapter compares the results that can be obtained with classical techniques against the results that alternative linear search techniques such as the Simultaneous Perturbation Stochastic Approaches (SPSA) algorithm can achieve. Authors start from the work reported by Gedi et al. 2015 to implement the SPSA algorithm. The experiments allow authors to affirm that for this case study, the SPSA is capable of equalizing, even improving the results reported by the authors.

Optimization of a Spectrophotometric Flow Injection

This chapter presents the optimization of the hydrodynamic and chemical parameters of the FIA system in the determination of copper and manganese in wine samples by VIS spectrophotometry. This technique has been based on the injection of liquid samples in the non-segmented movement, within a continuous carrier current of a suitable liquid. The injected sample forms a zone that disperses on its way to a detector. The later continuously records the absorbance or other physical parameters, since it continuously passes the sample material through the flow cell, using the factorial designs Plackett-Burman, Box-Behnken, and the factorial design 2^4. The methods have the advantages of low-cost, easy availability of chemicals, and instrumentation and straightforward application to real samples.

Two-Level Factorial Designs

The term design of experiments in analytical chemistry is associated to the establishment of adequate experimental conditions when working in the laboratory or process conditions used in industry to improve the instrumental conditions and/or extract the highest information from the experimental data. This chapter presents practical problem-solving strategies used to obtain a product or chemical process with desirable characteristics in an efficient mode, focused on the use of full and fractional (2-level) designs. The information is presented as a tutorial and the main advantages and disadvantages are presented and discussed, emphasizing the effect of reduction of experimentation in the data quality.

Optimization of Injection Molding Process Parameters via Design of Experiments

The validation of processes is an innovative methodology where a process has been submitted to scrutiny to guarantee the products comply with the specifications of the company and the norms of the country of consumption. In the medical industry, this process is considered as a regulatory requirement, however, this also helps to improve quality, eliminate waste, and reduce costs, among other things. This chapter applied the methodology of process validation in a medical device company; the engineering tests were used in the company's clean room, using an injection molding machine and tests of several parameters were used even without being validated to know which are the best run and the best parameters, for its daily use. This project addresses the validation of the blood filter process by injection molding. The Design of Experiments applied was a 2K factorial design with central points where the replicas consisted of five of 45 in total for the three dimensions. The pieces are shared for those three dimensions that are being evaluated.