Search results

In the fast paced PCB industry of today windows of opportunity are short. One needs to be able to find quickly the key variables to a new process or an existing process so that the capability requirement can be met. Guesswork and traditional experimental design approaches will not work. Control charts by themselves will not work. Very large experimental studies will not work. What will work are simple, well defined, statistically designed experiments. This paper is an example of how simple, statistically based experiments were used to reduce haloing on Teflon® circuit boards. The drilling and plating processes using different laminate materials were investigated using Box‐Wilson and Plackett‐Burman experimental designs. Different data analysis techniques such as confidence intervals, scree plots, analysis of variance tables and analysis of means charts were used to determine the true significant (key) variables and the insignificant (non key) variables. An effective experimental study must have a capable measurement system. A method of determining the measurement system capability and improving it for haloing using isoplots is presented. In the end, two economically feasible paths to reduce the haloing problem were found.

The purpose of this paper is to optimize production of cellulase enzyme from agricultural waste by using Aspergillus fumigatus JCF. The study also aims at the production of bioethanol using cellulase and yeast.

Cellulase production was carried out using modified Mandel’s medium. The optimization of the cellulase production was carried out using Plackett-Burman and Response surface methodology. Bioethanol production was carried out using simultaneous saccharification and fermentation.

Maximum cellulase production at optimized conditions was found to be 2.08 IU/ml. Cellulase was used for the saccharification of three different feed stocks, i.e. sugar cane leaves, corn cob and water hyacinth. Highest amount of reducing sugar was released was 29.1 gm/l from sugarcane leaves. Sugarcane leaves produced maximum bioethanol concentration of 9.43 g/l out of the three substrates studied for bioethanol production.

The present study reveals that by using the agricultural wastes, cellulase production can be economically increased thereby bioethanol production.

β-Carotene is the most appropriate and significant precursor of vitamin A. Synthetic carotene supplements have been known to pose a threat to human health, making natural sources such as the indefensible choice for the production and extraction of carotene.

This study considers Blakeslea trispora, a filamentous fungus, as a source of production of carotenoids by fermentation and wet and dry mycelium were used to analyse and obtain better extraction results.

In this study, natural oils such as soy oil and cottonseed oil were incorporated into fermentation media to increase the production of carotene. For the optimization process, Plackett–Burman and one-factor-at-a-time (OVAT) models were identified as being of great value.

OVAT was carried out for corn starch because it plays a major role in the production of carotene and the corn starch at 30 g/L concentration has shown the maximum activity of 3.48 mg/gm. After optimizing process variables, submerged fermentation was eventually carried out under highly controlled media conditions. The resulting product was quantified using UV spectroscopy and extraction of carotene has been observed in the presence of various solvents. Among a range of solvents used, the methylene Di chloride produced-carotene at 86% recovery at a significantly lower temperature of 35°C.

The paper's aim is to illustrate the use of a technique that can help researchers choose which techniques, and at what level, to employ in an internet‐based survey.

A screening experiment, designed as a Plackett‐Burman design, is used to study main effects of 11 techniques for increasing survey response. Three measures of effect used are click rate, completion rate, and response rate. A convenience sample of students at a large university in New Zealand is used.

Follow‐up had significant impact on click rate; incentive and pre‐notification had a significant impact on completion rate; no technique had significant effect on response rate.

Main effects are examined. Also, a limited number of approaches for each technique are studied.

This paper illustrates the use of a methodology that researchers, practitioner, and academics alike, can use to select techniques to employ in an internet survey. This is the first known application of the technique for selecting data collection techniques in marketing.

This paper aims to present an evaluation method for energy-absorption characteristics of thin-walled composite structures with random uncertain parameters.

The mechanical properties of T700/3234 are obtained by material performance tests and energy-absorption results are obtained by quasi-static crushing tests of thin-walled composite circular tubes. The indicators of triggering specific load (TSL) and specific energy absorption (SEA) are introduced and calculated to determine the energy-absorption characteristics and validate the probability finite element analysis model. The uncertainty in the parameters contain the machining tolerance for the thickness and inner diameter of composite circular tubes and are associated with the composite material system. The Plackett–Burman method is used to choose the measurement parameters. Then, the response surface method is used to build a second-order function of random uncertain parameters versus TSL/SEA, and the Monte Carlo method is finally used to obtain the probabilities of TSL and SEA.

The finite element models can accurately simulate the initial peak load, load-displacement curve and SEA value. The random uncertain parameter method can be used to evaluate the energy-absorption characteristics of thin-walled composite circular tubes.

The presented evaluation method for energy-absorption characteristics of thin-walled composite structures is an approach that considers uncertain parameters to increase the simulation accuracy and decrease the computational burden.

This methodology considers uncertain parameters in evaluating the energy-absorption characteristics of thin-walled composite structures, and this methodology can be applied to other thin-walled composite structures.

A structured customer-driven and integrative methodology to develop materials is described. The proposed methodology is aimed to drive analysis and prioritization of the multiple variables involved in a new application case for 3D printing, which involves the development of a new alumina-starch-based powder.

The development of new powder mixture designed for 3D printing of refractory supports for metal casting moulds is presented. The quality function deployment (QFD) method was applied. Inputs for QFD analysis were found using total quality management tools. Using this approach, six process and material variables were considered to drive a prioritization analysis using a Plackett-Burman Design of Experiment (DOE) array. As performance parameter, compressive resistance was measured and assessed.

QFD analysis delivered standardized procedures, irrelevant factors and target values for intermediate step parameters. Sintering parameters were found to be the most influencing over compressive resistance.

The methodology was based upon a materials development case for 3D printing.

Knowing in advance the influence of every affecting factor of the process provides a closer control on variability of final part properties, which is a key issue to launch parts into industrial applications. Quality planning and documentation in advanced is the basis for all the quality system of the new additive manufacturing (AM) process to be created.

Procedures for quality planning and control were proposed. This study, as methodological research, intends to introduce industrial engineering practices and quality management routines for AM material/process developers.

The purpose of this paper is to demonstrate the power of experimental design as a technique to understand and evaluate the most important factors which influence teaching effectiveness for a postgraduate course in a higher education (HE) context.

The methodology involves the execution of a case study in the form of an experiment in a business school setting. The experiment was carried out with the assistance of over 100 postgraduate students from 26 countries. The data were collected over a two year period (2015 and 2016) from a postgraduate course offered by the same tutor for repeatability reasons.

The key findings of the experiment have clearly indicated that students’ perceptions of teaching effectiveness based on intuition and guesswork are not identical to the outcomes from a simple designed experiment. Moreover, the results of the experiment provided a greater stimulus for the wider applications of the technique to other processes across the case study HE sector.

One of the limitations of the study is that the experiment was conducted for a popular postgraduate course. It would be beneficial to understand the results of the experiment for less popular postgraduate courses in the university in order to drive improvements. Moreover, this research was conducted only for postgraduate courses and the results may vary for undergraduate courses. This would be an interesting study to understand the differences in the factors between undergraduate and postgraduate teaching effectiveness.

The outcome of this experiment would help everyone who is involved in teaching to understand the factors and their influences to improve students’ satisfaction scores during the delivery of teaching.

This paper shows how experimental design as a pure manufacturing technique can be extended to a HE setting.

Response surface methodology (RSM) is used for optimality analysis of the cost coefficients in mixed integer linear programming. This optimality analysis goes beyond traditional sensitivity and parametric analysis in allowing investigation of the optimal objective function value response over pre‐specified ranges on multiple problem parameters. Design of experiments and least squares regression are used to indicate which cost coefficients have the greatest impact on the optimal total cost surface over the specified coefficient ranges. The mixed integer linear programming problems of interest are the large‐scale facility location and allocation problems in supply chain optimization. A system that automates this process for supply chain optimization at PFS Logistics Consulting is discussed and an example is presented.

The increasing accumulation of synthetic plastic waste in oceans and landfills, along with the depletion of non-renewable fossil-based resources, has sparked environmental concerns and prompted the search for environmentally friendly alternatives. Biodegradable plastics derived from lignocellulosic materials are emerging as substitutes for synthetic plastics, offering significant potential to reduce landfill stress and minimise environmental impacts. This study highlights a sustainable and cost-effective solution by utilising agricultural residues and invasive plant materials as carbon substrates for the production of biopolymers, particularly polyhydroxybutyrate (PHB), through microbiological processes. Locally sourced residual materials were preferred to reduce transportation costs and ensure accessibility. The selection of suitable residue streams was based on various criteria, including strength properties, cellulose content, low ash and lignin content, affordability, non-toxicity, biocompatibility, shelf-life, mechanical and physical properties, short maturation period, antibacterial properties and compatibility with global food security. Life cycle assessments confirm that PHB dramatically lowers CO₂ emissions compared to traditional plastics, while the growing use of lignocellulosic biomass in biopolymeric applications offers renewable and readily available resources. Governments worldwide are increasingly inclined to develop comprehensive bioeconomy policies and specialised bioplastics initiatives, driven by customer acceptability and the rising demand for environmentally friendly solutions. The implications of climate change, price volatility in fossil materials, and the imperative to reduce dependence on fossil resources further contribute to the desirability of biopolymers. The study involves fermentation, turbidity measurements, extraction and purification of PHB, and the manufacturing and testing of composite biopolymers using various physical, mechanical and chemical tests.

This article presents a novel case study that analyzes the applicability of DoE in the curling sport in order to improve their own performance and the performance of its athletes. Specifically, this study analyzes the most important factors to increase accuracy and precision in the draw game with curlers' opinions. It was decided to use the “Last Stone Draw (LSD)’ as an appropriate play situation.

Specifically, this study analyzes most important factors to increase accuracy and precision in the draw game with curlers opinions from the German Curling association. Three research techniques were used in this study: case study, interviews and a well-designed experiment. The analysis through the use of DoE includes a measurement system analysis, an initial variance test between two players, a screening and a characterization experiment.

The results obtained from DoE suggest that the factors routine, stress, release, balance, and the previous play situation have a substantial impact on the score of the player's draw game. However, no factor has a statistically significant impact on the average distance to the center of the target. Moreover, the DoE analysis also concludes that the accuracy and precision of the player's performance is not affected equally by all analyzed factors, but they turn into highly significant when examining their relationship to the other factors.

The findings of this study can be beneficial to other sports events in improving the performance. Moreover, DoE has proved to be an invaluable tool for many people in the German Curling Association in understanding the factors which influence the curlers performance and also factors which do not affect the curlers performance.

This research attempts to contribute to the existing sports management literature by identifying a way in which DoE can be an effective tool in non-manufacturing settings for identification of most important factors which influence the curling performance.