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Dr Genichi Taguchi is a Japanese engineer and quality consultant who has promoted the use of statistical design of experiments for improving process/product quality at minimal costs. Taguchi has developed a practical and strategic approach for designing quality into products and processes at the product planning, design and development stages, which is often referred to as off‐line quality control. Although many companies in Europe and the USA have used the Taguchi approach to statistical design of experiments with success, very few applications of this method are realised in countries such as the Czech Republic. This paper reports the applications of experimental design advocated by Taguchi in two manufacturing companies in the Czech Republic. The results of the study are stimulating and will lead to wider applications of this methodology for tackling process and quality‐related problems in the Czech Republican industries in the near future.

Overall equipment effectiveness (OEE) provides a quantitative metric based on the elements availability, performance and quality for measuring the performance effectiveness of individual equipment or entire processes. Although these elements are important, other performance factors such as the efficient use of raw materials and the production environment (e.g. production system, logistics, labour, etc.) in which the equipment or process operates may also have a significant contribution to process performance. The purpose of this paper is to present an alternative measure derived from OEE, overall resource effectiveness (ORE), which considers these factors.

The paper reviews the OEE’s background and explores its limitations. Then, it shows the conceptual and mathematical development of the ORE measure and the formulas used for its calculation. Empirical and simulation-based investigations and applications of ORE are carried out through two cases study for its validation.

The results derived from both the empirical and simulation-based investigations demonstrate that OEE may not be an appropriate measure for some specific processes and that ORE may offer a more complete perspective on and information of key performance indicators.

ORE can provide production managers with more complete information concerning the performance of their processes. This will allow them to take better decisions regarding the management and actions needed to improve their processes.

This paper presents a novel and alterative approach to measure the performance of manufacturing equipment and processes.

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.

The popular reflow day was repeated at Henley and commenced with Mike Judd giving an overview of current reflow techniques.

New forms of retailing present different pricing challenges. The selling of college textbooks over the Internet represents an ideal case study of the different elements that enter into consumer’s price equation. College students were asked to rate the likelihood of purchase of a text given different profiles of sellers and their offerings. Using conjoint analysis, estimates of consumer tradeoffs were calculated. In‐stock status at the college bookstore was the most important variable, followed by buy‐back policies/guarantees. Price of the text was the third most important variable. Implications for both bookstores and on‐line retailers are presented.

The purpose of this paper is to evaluate the agility performance level of manufacturing supply chains using Taguchi loss functions (TLFs) and design of experiment (DoE).

The proposed methodology is used for capturing the various agility losses using appropriate TLFs and the aggregated agility loss is calculated at different situations using DoE. The aggregated agility loss is analysed for comparing manufacturing supply chain agility performance.

The proposed methodology was applied to three Indian auto component supply chains, i.e. X, Y and Z. In total, 27 experiments were carried out using DoE and obtained results show that agility performance level is the highest for X followed by Z, whereas agility performance level is the least for Y.

The proposed methodology is generic in nature and can be applied to a specific environment for comparing performance of different supply chains. The user has to identify the relevant agility enablers and capture the appropriate TLFs for the specific environment in which agility performance level has to be calculated and compared.

The proposed methodology provides an effective approach for evaluating agility performance. It can be used by the supply chain manger to assess the supply chain agility performance level of own company with its competitors. These comparisons will help the manufacturing company to find the areas where it should focus.

Many studies and researches related to implementation and evaluation of agile manufacturing are reported in the literature but very few studies are available for evaluating the supply chain agility performance. This study will definitely provide a guideline for measuring and comparing manufacturing supply chain agility performance in general and Indian automotive supply chain in specific.

Approximation techniques were used instead of expensive computing analysis in a traditional parametric design optimization of a complex system. A Kriging meta‐model was utilized, which enabled the fit of approximated design characteristics for a complex system such as turbine blades that incorporate a large number of design variables and non‐linear behaviors. This paper aims to discuss these issues.

The authors constructed a Kriging meta‐model with a multi‐level orthogonal array for the design of experiments, which were used to optimize the fatigue life of turbine blades under cyclic rotational loads such as centrifugal force. By combining a seven‐level orthogonal array with the Kriging model, the non‐linear design space of fatigue life was explored and optimized.

A computer‐generated multi‐level orthogonal array provided a good representation of the non‐linear design space information. The results show that not only was the fatigue life of the leading edge of the blade root significantly improved, but also that the computing analysis was effective.

To maximize the fatigue life of the turbine blade, the three‐design variables with seven factor levels were optimized via a Kriging meta‐model. As with the optimization technique, a desirability function approach was adopted, which converted multiple responses into a single response problem by maximizing the total desirability.

In the Taguchi’s experimentations, orthogonal arrays, interaction tables, and linear graphs are provided for planning experiments, but they become quite unwieldy when the number of runs is large. The purpose of this article is to propose a quick and easy method for obtaining two‐factor interaction columns in two‐level orthogonal arrays. Geometrical designs proposed by Plackett and Burman are two‐level orthogonal arrays and can be obtained very easily by a successive doubling method. Based on the property of doubling, a NR method using a number representation system whose base is a power of 2 is derived in this article for obtaining two‐factor interaction columns in geometrical designs. Furthermore, since Taguchi’s two‐level orthogonal arrays are obtainable by successive doubling with some column permutations, it is shown that their two‐factor interaction columns can be obtained directly by using the NR method without looking up tables.

This paper aims to study a generalized type of mixed-model assembly line with multi-manned workstations where multiple workers simultaneously perform different tasks on the same product. This special kind of assembly line is usually utilized to assemble different models of large products, such as buses and trucks, on the same production line.

To solve the mixed-model multi-manned assembly line balancing problem optimally, a new mixed-integer-programming (MIP) model is presented. The proposed MIP model is nondeterministic polynomial-time (NP)-hard, and as a result, a simulated annealing (SA) algorithm is developed to find the optimal or near-optimal solution in a small amount of computation time.

The performance of the proposed algorithm is examined for several test problems in terms of solution quality and running time. The experimental results show that the proposed algorithm has a satisfactory performance from computational time efficiency and solution accuracy.

This research is the very first study that minimizes the number of workers and workstations simultaneously, with a higher priority set for the number of workers, in a mixed-model multi-manned assembly line setting using a novel MIP model and an SA algorithm.

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.