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Many industrial engineers perform one‐factor‐at‐a‐time (OFAT) experiments to examine situations of process improvement and for problem‐solving activities. However, OFAT experiments can prove to be inefficient and unreliable, leading to false optimal conditions. Moreover, they often consist largely of “trial and error”, relying on luck, intuition, guesswork and experience for their success. Design of experiments (DOE) takes an alternative, more structured approach. DOE is a powerful technique for discovering a set of process or design variables which are most important to the process/product/system and then assisting experimenters to determine at what levels these variables should be set/kept to optimise performance. In order to demonstrate the power of designed experiments over the traditional OFAT approach, the authors use a simple catapult experiment. They suggest that such an experiment could act as a powerful weapon in the training of engineers and managers who might be intimidated by a more “up front” statistical approach.

This study aims to investigate the influence of process parameters of wire electrical discharge machining (WEDM) of Nimonic75. Nimonic75 is a Nickel-based alloy mostly used in the aerospace industry for its strength at high temperature.

One factor at a time (OFAT) approach has been used to perform the experiments. Pulse on time, pulse off time, peak current and servo voltage were chosen as input process parameters. Cutting speed, material removal rate and surface roughness (Ra) were selected as output performance characteristics.

Through experimental work, the effect of process parameters on the response characteristics has been found. Results identified the most important parameters to maximize the cutting speed and material removal rate and minimize Ra.

Very limited research work has been done on WEDM of Nickel-based alloy Nimonic75. Therefore, the aim of this paper to conduct preliminary experimentation for identifying the parameters, which influence the response characteristics such as material removal rate, cutting speed, Ra, etc. during WEDM of Nickel-based alloy (Nimonic75) using OFAT approach and found the machinability of Nimonic75 for further exhaustive experimentation work.

Experiments are fundamental to enhancing understanding of the complex industrial processes which we deal with every day. Experimental Design (ED) is a very powerful tool that assists engineers and scientist to discover a set of variables which are most important for a process and thereby provide a great insight into the way a process or system works. It is superior to traditional scientific approach or One‐Factor‐At‐A‐Time (OFAT) approach to experimentation, still often used today. This paper illustrates some fundamental and practical issues that every industrial engineer should know about ED. These issues include factor effects, interactions, response or quality characteristics, randomisation, replication, analysis of variance and contour plots. The paper also presents an example to demonstrate the above issues. The problems and gaps in ED in the state‐of‐the‐art will also be highlighted.

Robust design (RD) is a powerful methodology for making products’ performance insensitive to variations in manufacturing conditions, environmental variations and product‐to‐product variation. Although it has been widely accepted for tackling variability problems in manufacturing processes, research has shown that very little has been done on the application of such a powerful methodology in the UK manufacturing sector within the new product development process (NPDP). Engineers and scientists in the UK organizations are far more likely to use the traditional one‐factor‐at‐a‐time (OFAT) approach to experimentation than RD. This paper investigates why RD is not commonly accepted and applied in the UK manufacturing organizations as opposed to Japan and even the USA today. The paper will also illustrate what benefits could be achieved if RD principles are effectively applied in the NPDP in manufacturing organizations.

AA2014 is a copper-based alloy and is typically used for production of complex machined components, given its better machinability. The purpose of this paper was to study the effects of variation in weight percentage of ceramic Al₂O₃ particulates during electrical discharge machining (EDM) of stir cast AA2014 composites. Scanning electron microscopy (SEM) examination was carried out to study characteristics of EDMed surface of Al₂O₃/AA2014 composites.

The effect of machining parameters on performance measures during sinker EDM of stir cast Al₂O₃/AA2014 composites was examined by “one factor at a time” (OFAT) method. The stir cast samples were obtained by using three levels of weight percentage of Al₂O₃ particulates, i.e. 0 Wt.%, 10 Wt.% and 20 Wt.% with density 1.87 g/cc, 2.35 g/cc and 2.98 g/cc respectively. Machining parameters varied were peak current (1-30 amp), discharge voltage (30-100 V), pulse on time (15-300 µs) and pulse off time (15-450 µs) to study their influence on material removal rate (MRR), tool wear rate (TWR) and surface roughness (SR).

MRR and SR decreased with an increase in weight percentage of ceramic Al₂O₃ particulates at the expense of TWR. This was attributed to increased microhardness for reinforced stir cast composites. However, microhardness of EDMed samples at fixed values of machining parameters, i.e. 9 amp current, 60 V voltage, 90 µs pulse off time and 90 µs pulse on time reduced by 58.34, 52.25 and 46.85 per cent for stir cast AA2014, 10 Wt.% Al₂O₃/AA2014 and 20 Wt.% Al₂O₃/AA2014, respectively. SEM and quantitative energy dispersive spectroscopy (EDS) analysis revealed ceramic Al₂O₃ particulate thermal spalling in 20 Wt.% Al₂O₃/AA2014 composite. This was because of increased particulate weight percentage leading to steep temperature gradients in between layers of base material and heat affected zone.

This work was an essential step to assess the machinability for material design of Al₂O₃ reinforced aluminium metal matrix composites (AMMCs). Experimental investigation on sinker EDM of high weight fraction of particulates in AA2014, i.e. 10 Wt.% Al₂O₃ and 20 Wt.% Al₂O₃, has not been reported in archival literature. The AMMCs were EDMed at variable peak currents, voltages, pulse on and pulse off times. The effects of process parameters on MRR, TWR and SR were analysed with comparisons made to show the effect of Al₂O₃ particulate contents.

This paper aims to illustrate an application of Taguchi method of experimental design (TMED) for the development of a new ignition coil for an automotive vehicle.

The application of TMED for optimisation of manufacturing processes has been widely published in the existing literature. However, the applications of TMED in the design and development of new products are not yet widely reported. This case study presents the results of a designed experiment which utilises a 16‐trial experiment to study 14 design parameters and one interaction. The case study strictly follows a systematic and disciplined methodology outlined in the paper.

The optimal settings of the critical design parameters are determined. The optimal settings have resulted in increased customer satisfaction, improved market share and low defect rate in the hands of customers.

Although the optimal levels are determined from one large experiment, it was unable to determine the true optimal values of each design parameter.

Manufacturers may use TMED to optimise processes (either design or manufacturing) without expensive and time‐consuming experimentation. This case study demonstrates the true power of a well planned and designed experiment over the traditional varying one‐factor‐at‐a‐time approach to experimentation which is rather unreliable, not cost‐effective and may lead to false optimal conditions.

The paper provides an excellent resource for those people who are involved in the design optimisation of a new product.

The purpose of this paper is to model the corrosion rate behavior for two ferrous materials, carbon steel AISI 1020 and stainless steel AISI 304, immersed in ferric sulfate and ferric chloride solutions using D-optimal design with response surface methodology.

Experimental design addresses two factors (concentration and contact time) with multilevel categories, in order to predict and compare the corrosion rates of the studied materials immersed in flocculants solutions. A corrosion rate of specimens was calculated from mass loss determinations.

The authors used a polynomial model to fit the experimental values, thereby predicting significantly higher corrosion rates in ferric chloride solutions, as compared to ferric sulfate.

The authors propose a high fidelity model of the corrosion rate of each carbon steel and stainless steel material using D-optimal design with a response surface method (RSM).

The purpose of the article is to present the results of a critical literature review (CLR) on Design of experiments (DoE) in the service industry.

A critical review of existing literature review across various databases including Scopus, Web of Science, Google Scholar and Emerald Insight were searched for the identification of relevant papers. The authors searched relevant journal articles for a time period of 25 years (1994–2019).

A total of 29 industry case studies of DoE applications were identified spanning healthcare, retail, logistics, education, marketing, after sales and catering business. The industrial experimentation strategies adopted by the case study organisations were screening, factorial designs, Taguchi, response surface method and split-plot. It was apparent that there are only a handful number of papers showing the applications of DoE across the service sector and this motivates for pursuing further research into this topic by the authors.

The findings of the study can be very useful for middle and senior managers to understand the benefits of implementing this powerful technique for increased understanding of service processes, as well as for optimising service performance. Moreover, the paper presents some of the fundamental challenges, as well as skills needed for the successful application of DoE.

To the best of our knowledge, this is the first CLR on DoE and its applications in the service sector. The findings of the study can be beneficial to both academic and industrial communities to understand some of the challenges and fundamental gaps which need to be tackled in the future.

Statistical process control (SPC) is widely applied for control and improve processes in manufacturing, but very few studies have reported on the successful application of SPC in the food industry, in particular. The purpose of this paper is to critically assess the status of SPC in the UK food manufacturing industry and to suggest future research avenues.

A research project was carried out in the UK food manufacturing sector through questionnaires. The results of the study were analysed using descriptive statistics and statistical tests to be applied in the hypothesis testing.

Findings revealed that 45 per cent of the respondents are SPC users and x ¯ -R and x ¯ -S charts are the most commonly applied SPC charts in this industry. It was determined that top management commitment is the most critical factor, while lack of SPC training is the most alarming challenge, and lack of awareness of SPC and its benefits are the main reasons for the food companies not implementing SPC.

The study considered only the food manufacturing companies. Future research could be addressed toward the food service and food supply chain.

The paper provides information to food companies in the UK on most common practiced and important quality tools, SPC charts and critical success factors in the food industry. Moreover, the most challenging factors of SPC implementation in the food industry are presented.

This study depicted the current state of SPC practices in the food industry and the process performance in SPC and non-SPC companies is compared.

Industrial experiments have shown an unprecedented success for improving the product and process quality in many manufacturing organisations. This paper provides some useful and practical tips to industrial engineers with limited knowledge in experimental design (ED) for making industrial experiments successful in their own organisations. ED is a powerful tool which can be used to achieve breakthrough improvements in product quality and process effectiveness. The purpose of the paper is to stimulate the engineering community to start applying ED for tackling quality control problems in key processes they are dealing with everyday.