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Reviews a real‐life investigation carried out on copper coating of CO⊂2 welding wire. The major quality problems were non‐uniformity in coating thickness and other associated problems. The factors identified as responsible are speed of drawing the wire, acid, ferrous and copper sulphate. Describes three stages of the study. The results obtained revealed a number of interesting facts about the process. The extent to which the copper coating is influenced by these factors independently and interactively was vividly brought out by factorial experiments, fractional factorial experiments and standard orthogonal arrays. These results show various intricate dynamics of interest to a process controller.

During the past few years, statistical process control and experiment design concepts have taken a prominent place within the industry. The use of such tools within the Motorola, GEG manufacturing environment, has grown to the point where reflow and wave solder process development and optimisation has significantly benefited. The ability to evaluate statistically and model various known and unknown phenomena has provided GEG's manufacturing technology with a series of very powerful tools to aid in process control and development. The primary purpose of this paper is to present the various approaches used by GEG to implement the previously mentioned statistical tools, with respect to the development of infra‐red (I‐R) reflow solder processes and enhancement of certain quality characteristics associated with wave soldered printed wiring boards (PWBs). Beyond specific GEG applications, the paper discusses the role of statistically designed experiments and process control methods as a vehicle for providing answers to complex manufacturing problems. In addition, a discussion of the mathematical and graphical methods underlying the interpretation of quantitative data is presented. Perhaps the most important benefit derived from the use of statistics to solve manufacturing and quality problems is related to decision making. When experiments are conducted to isolate unwanted sources of process and product variation, decisions must be made to determine whether or not certain experimental effects are important. Through the application of statistics, the researcher can ascertain the mathematical probability associated with the random chance occurrence of various experimental effects. With this knowledge, the researcher can make decisions with known degrees of risk and confidence. Without such knowledge, an organisation might possibly expend valuable resources and derive no direct benefit. Ultimately, the principal reason for applying statistical methods and procedures is to increase quality and yield, while simultaneously reducing costs.

The purpose of this paper is to improve the key quality performance of the terminal of earphone in an electronic company.

Sequential experimental designs are employed. Significant input variables are found through a full factorial design. Then a response surface model is constructed considering curvature in the linear model.

Optimized key input variables’ parameters are found using the response surface model. The key quality performance, coplanarity of the terminal of earphone has been improved.

Instead of running a full factorial design in the first stage, a fractional factorial may be used to reduce experimental runs.

The paper presents a good solution for reducing defects caused by large coplanarity of a kind of earphone terminal.

The methodology used in this case can be easily extended to similar cases.

Commercial pressure has forced improvements in the reduction of press down time. One restraining factor for the flexographic printing process has been the lack of predictability and consistency. The results of a factorial designed experiment, are reported in this paper. Investigations into the complex interactions of many variable factors that take place during the printing process were carried out. Various statistical methods were employed for the design of the experiment and for the interpretation of experimental data generated. The results of the investigation have been used to optimise the flexographic printing techniques to significantly manipulate the properties of various production components for the end‐use application to enhance the plates printing performance and consistency.

The purpose of this paper is to focus the application of design of experiments (DOE) using industrial equipments, reinforcing idea that non‐statistical aspects in planning and conducting experiments are so important as formal design and analysis.

Two case studies are presented to illustrate typical industrial applications and difficulties. Supported on these case studies and literature, this paper presents guidelines to planning, conducting and analysis involving technical and organizational aspects.

Solving problems in industry, including in companies recognized as competent in the respective industrial sector, is not just a question of applying the right technique. Ceramic industry case study illustrates how important are non‐statistical issues in DOE application. Paint industry case study illustrates the strong relationship of the results with incorporating presented guidelines into practice. Moreover, both case studies consolidating a fundamental advantage of DOE: experimentation provides more knowledge about products, processes and technologies, even in unsuccessful case studies.

Unsuccessful cases studies are very useful for identifying pitfalls and others limitations. This paper highlight difficulties aroused from non‐statistical aspects, although it is possible to find unsuccessful case studies due to statistical issues also. So, papers illustrating inadequate application of statistical techniques are welcome.

Successful DOE implementation depends on statistical and non‐statistical aspects. Although none of them shall be neglected, technical skills and technological knowledge about processes and products, management understanding of potential possibilities of statistical techniques and statistical fundamentals and knowledge about techniques of DOE must be ensuring to successful case studies in industrial setting.

This paper highlights non‐statistical aspects instead of the statistical ones. Tob overcome difficulties structured guidelines were designed to support DOE application in industrial setting.

Experimental design based on sound statistical principles offers economical means of investigating quality problems. Proper design is as important as sophisticated statistical analysis. Two properly designed but simple factorial experiments are described which led to significant quality improvement in wave‐soldering and carbonitriding processses.

The aim of this paper is to proposes a simple and unified method for generating the aliasing pattern of two‐ and three‐level fractional factorial designs be they regular or non‐regular. The paper also demonstrates how the aliasing patterns obtained using the postulated method can be used to render the main measures of aliasing severity.

The proposed method is based on viewing the fractional factorial designs geometrically. It entails regarding the columns of any design as vectors. On the premise that any two vectors are orthogonal if they are at right angle and bearing in mind that aliasing is a form of departure from orthogonality, the proposed method determines the degree of aliasing between any two columns by assessing the extent to which the angle between them differs from 90°.

Three examples were used to illustrate how the proposed method can be applied and to validate its results. The first dealt with a regular two‐level L₈ 2⁵⁻² design whereas the second concerned a non‐regular two‐level L₁₂ design used to study five‐factors, and the third example is based on a non‐regular L₁₈ design employed to examine three‐factors at three‐levels. For each of these, the aliasing pattern generated using the proposed method matches the one obtained using the conventional methods.

A recent empirical study of how experimental design is applied in certain Manufacturing Engineering journals revealed that aliasing is rarely investigated. One possible reason for this is the difficulty associated with comprehending the conventional methods of dealing with aliasing particularly in the cases where non‐regular two‐ and three‐level orthogonal arrays are used. The proposal of a simple and unified method for dealing with aliasing should encourage the researchers and practitioners to assess aliasing when performing their experiments.

Statistical experimental design (SED) can be used as an analytical tool to investigate the effect of a range of PCB processing parameters (variables) on certain final properties (responses). Compared to the “typical” method of carrying out experimental trials, the use of SED can identify “interactions” between variables that may not become apparent without extensive testing otherwise. The SED route also offers a measure of experimental error within the process and can suggest ways to optimise the process, with a reduced number of experimental runs. An application of the SED process is also discussed regarding the evaluation and optimisation of a horizontal liquid photoimageable solder mask (LPISM) spraying process in accordance with certain key factors.

The purpose of this article is to demonstrate the application of the tools and techniques of Quality by Design (QbD) approach in an Indian pharmaceutical drug product manufacturing company and to understand the challenges, managerial implications and lessons learned while implementing this initiative.

This work adopts the Action Research methodology for impurity reduction in a drug product manufacturing company in India by using the tools and techniques of QbD approach. Various QbD tools like Design of experiments, process capability evaluation and control charts were effectively utilized for the study.

As a part of QbD implementation in the organization, a specific drug product was identified and the impurity level in the product was studied. Significant variables impacting the impurity were identified and the optimum levels for the significant variables were identified through design of experiments. The solutions were implemented and the impurity levels were reduced significantly.

Even though the article is based on a single case study related to tools and techniques of QbD in a single organization in India, the identified problem is a generic product quality related issue for any pharmaceutical drug product manufacturing company. Hence the findings of this research are applicable to pharmaceutical drug manufacturing industry in general.

This article illustrates the systematic usage of various tools and techniques of QbD methodology in a pharmaceutical drug product manufacturing company. The usage of Design of Experiments for process optimization and application of other tools and techniques are ready references for the practitioners and novice users in the field.

The print fault “dot bridging” reduces the printing press efficiency. This study was designed to find the best combination of materials used in normal production which would reduce or eliminate the problems thus increasing efficiency.

Various statistical methods were used to design the experiments and to analyse the experimental results. The experiment included all of the factors which were considered to have an effect on the “dot bridging” print fault.

The most important conclusion that can be drawn from the results is that the complex interactions between factors included in the process can be characterised. The experiment proved that the problem was not random. The data gathered during the experiment had a direct correlation with the psychometric results. Various factors included in the experiment were found to have a significant influence on print density and print contrast. Contrast and density were selected for analysis as ink film thickness was thought to have an influence on the best looking print samples and the “dot bridging” print fault.

The results of the experiment were used to optimise the production process particularly the platemaking technique. Data from further experiments would help to optimise more process parameters.

Minitab computer software was used to analyse the results of the experiment thus making it easier to communicate the results to non‐scientific production staff.

This was the first time that the printer concerned had used a scientific approach to problem solving. The end result for the printer was an increase in production efficiency which saved the printer a considerable amount on money.