STATISTICAL EXPERIMENTAL DESIGN IN THAI CERAMIC AND GLASS RESEARCH
Abstract
The word “Ceramic” is derived from the Greek word “keramos” which means “burning stuff” or “burned earth” (Kingery et al., 1976). Ceramics are defined as inorganic nonmetallic solid materials. Ceramics are typically crystalline compounds formed between metallic and nonmetallic elements such as aluminum and oxygen (alumina-Al2O3), beryllium and carbon (beryllium carbide-Be2C), and silicon and nitrogen (silicon nitride-Si3N4). Glasses are special types of ceramics which have amorphous or non-crystalline structures. Most people think of ceramic as pottery, porcelain, whiteware, tile, brick, cement, enamel, glass, abrasive, and refractory. The above mentioned are referred to as “traditional or silicate-based ceramics”. While these traditional products have been and continue to be important to society, a new class of ceramics has emerged in the last 40 years (Kingery et al., 1976). This class of ceramic is “new or advanced ceramics”. They are of particular interest because they have outstanding properties. Examples of these new ceramic materials are piezoelectric, pyroelectric, ferroelectric, dielectric, ferrimagnetic, glass-ceramic, nitride, carbide, hydroxyapatite, and bone-cement, among others. They were developed in order to fulfill particular needs. These needs were for special electrical properties, temperature resistance, superior mechanical properties, and greater chemical resistance. Advanced ceramics are being used for several applications including computer components, microwave and electronic parts, nuclear fuel, space shuttle tiles, and artificial bones and teeth, among others.
The important goals in ceramic research are to reduce the cost and to improve the specific properties of products. Statistical experimental design and analysis are effective tools to assist ceramists to reach their stated forward looking goals. Statistical design of experiments is the process of planning the experiment so that appropriate data will be collected and statistically analyzed. These methods not only help ceramists to plan and conduct experiments but also assist them in analysis of the resulting data. With good experimental design and analysis, the maximum amount of information can be obtained from a minimum amount of collected data. As an example of such an experiment, suppose that a ceramist is interested in studying the effects of time (x1) and firing temperature (x2), as well as chemical composition (x3), on water absorption
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