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The use of a designed quality plan for application in the electrical power industry is presented. Some contributions of Taguchi’s technique in power process parameter design are reviewed. Recommendations are made for developing a quality‐training plan that will incorporate the design of experiments and description of training sources. A case study of the experiment design in the Hellenic power production process is discussed. Difficulties with design of experiments applications to the power process are outlined and suggestions are offered for resolving these difficulties.

In the vast majority of published papers, the optimal reactive power dispatch (ORPD) problem is dealt as a single-objective optimization; however, optimization with a single objective is insufficient to achieve better operation performance of power systems. Multi-objective ORPD (MOORPD) aims to minimize simultaneously either the active power losses and voltage stability index, or the active power losses and the voltage deviation. The purpose of this paper is to propose multi-objective ant lion optimization (MOALO) algorithm to solve multi-objective ORPD problem considering large-scale power system in an effort to achieve a good performance with stable and secure operation of electric power systems.

A MOALO algorithm is presented and applied to solve the MOORPD problem. Fuzzy set theory was implemented to identify the best compromise solution from the set of the non-dominated solutions. A comparison with enhanced version of multi-objective particle swarm optimization (MOEPSO) algorithm and original (MOPSO) algorithm confirms the solutions. An in-depth analysis on the findings was conducted and the feasibility of solutions were fully verified and discussed.

Three test systems – the IEEE 30-bus, IEEE 57-bus and large-scale IEEE 300-bus – were used to examine the efficiency of the proposed algorithm. The findings obtained amply confirmed the superiority of the proposed approach over the multi-objective enhanced PSO and basic version of MOPSO. In addition to that, the algorithm is benefitted from good distributions of the non-dominated solutions and also guarantees the feasibility of solutions.

The proposed algorithm is applied to solve three versions of ORPD problem, active power losses, voltage deviation and voltage stability index, considering large -scale power system IEEE 300 bus.

The primary aim of this article is to ascertain the modalities of leveraging Lean Six Sigma (LSS) for Industry 4.0 (I4.0) with special reference to the process industries. Moreover, it intends to determine the applicability of simulation-based LSS in the automation of the mineral water industry, with special emphasis on the robust design of the control system to improve productivity and performance.

This study adopts the action research methodology, which is exploratory in nature along with the DMAIC (define-measure-analyze-improve-control) approach to systematically unearth the root causes and to develop robust solutions. The MATLAB simulation software and Minitab statistical software are effectively utilized to draw the inferences.

The root causes of critical to quality characteristic (CTQ) and variation in purity level of water are addressed through the simulation-based LSS approach. All the process parameters and noise parameters of the reverse osmosis (RO) process are optimized to reduce the errors and to improve the purity of the water. The project shows substantial improvement in the sigma rating from 1.14 to 3.88 due to data-based analysis and actions in the process. Eventually, this assists the management to realize an annual saving of 20% of its production and overhead costs. This study indicates that LSS can be applicable even in the advent of I4.0 by reinforcing the existing approach and embracing data analysis through simulation.

The limitation of this research is that the inference is drawn based on a single case study confined to process industry automation. Having said that, the methodology deployed, scientific information related to optimization, and technical base established can be generalized.

This article is the first of its kind in establishing the integration of simulation, LSS, and I4.0 with special reference to automation in the process industry. It also delineates the case study in a phase-wise manner to explore the applicability and relevance of LSS with I4.0. The study is archetype in enabling LSS to a new era, and can act as a benchmark document for academicians, researchers, and practitioners for further research and development.

The purpose of this paper is to propose and validate a robust industrial control system. The aim is to design a Multivariable Proportional Integral controller that accommodates multiple responses while considering the process's control and noise parameters. In addition, this paper intended to develop a multidisciplinary approach by combining computational science, control engineering and statistical methodologies to ensure a resilient process with the best use of available resources.

Taguchi's robust design methodology and multi-response optimisation approaches are adopted to meet the research aims. Two-Input-Two-Output transfer function model of the distillation column system is investigated. In designing the control system, the Steady State Gain Matrix and process factors such as time constant (t) and time delay (?) are also used. The unique methodology is implemented and validated using the pilot plant's distillation column. To determine the robustness of the proposed control system, a simulation study, statistical analysis and real-time experimentation are conducted. In addition, the outcomes are compared to different control algorithms.

Research indicates that integral control parameters (K_i) affect outputs substantially more than proportional control parameters (K_p). The results of this paper show that control and noise parameters must be considered to make the control system robust. In addition, Taguchi's approach, in conjunction with multi-response optimisation, ensures robust controller design with optimal use of resources. Eventually, this research shows that the best outcomes for all the performance indices are achieved when Kp11 = 1.6859, Kp12 = −2.061, Kp21 = 3.1846, Kp22 = −1.2176, Ki11 = 1.0628, Ki12 = −1.2989, Ki21 = 2.454 and Ki22 = −0.7676.

This paper provides a step-by-step strategy for designing and validating a multi-response control system that accommodates controllable and uncontrollable parameters (noise parameters). The methodology can be used in any industrial Multi-Input-Multi-Output system to ensure process robustness. In addition, this paper proposes a multidisciplinary approach to industrial controller design that academics and industry can refine and improve.

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 quantify the effect of design parameters on the bullwhip effect and dynamic responses produced by a multi‐echelon supply chain with information sharing.

Taguchi design of experiments and system dynamics simulation are used to quantify the impact of a supply chain's design parameters, including degree of information sharing, on its dynamic performance, and the interactions that occur as the parameter values are varied.

Quantified relationships between supply chain design parameters and dynamic performance, including the bullwhip effect, are presented. Two parameters in particular, time to adjust inventory error and production lead time, are shown to have a particularly strong impact on the order variance compared to other parameters. However, there are several other significant findings.

Batching and capacity constraints are common causes of the bullwhip effect, but they are not included here. Future work should quantify the impact of these.

This paper presents a systematic way for quantifying and understanding the impact of supply chain design parameters on the bullwhip effect and dynamic responses, and their interactions. The experimental results provide practical understanding for supply chain managers.

Previous studies have identified causes of the bullwhip effect but little attention has been given to quantifying their impact and interactions. This paper makes a contribution towards filling this gap, using system dynamics simulation and Taguchi design of experiments.

The study aims to provide important insights into environmental attributes that are relevant to consumer's choices in purchasing canned tuna fish, and how much these attributes and socio-demographic individual characteristics relate to the frequency of consumption.

An online survey of 251 Italians was carried out. Socio-demographic variables and environmental attributes of the product that consumers pay attention to were considered in a two-step analysis: a cluster analysis used to create a segmentation of people's profiles that are further characterised; a binary logistic regression to assess the significance of attributes in relation to the frequency of canned tuna consumption.

Among attributes that respondents pay attention to when purchasing canned tuna, the country of origin is the aspect most considered, while other characteristics with a higher content of environmental sustainability received minimal attention. Three clusters emerged: the smallest one, insensitive to sustainability issues; an intermediate group which is mindful of sustainability attributes; and the biggest cluster which is “sustainability inconsistent.” Moreover, respondents who reported concerns about the environmental impacts of tuna production are less likely to consume the product than other consumers; attention paid to the method of farming, the presence of children and a young age show willingness to consume tuna.

This study contributes to the literature on canned tuna consumption by focusing on the attention that consumers pay to environmental product attributes in their purchasing choices. The relevance of this topic might be envisaged in relation to several environmental issues associated with tuna production and consumption, and to the economics and strategies of the tuna industry, being canned tuna among the most internationally traded seafood products.

The purpose of this paper is to investigate the impact of personality traits on the perceived usability evaluation of e-learning platforms. In specific, perceived usability levels of the educational platforms and tools used in primary and secondary education in Greece are demonstrated. The impact which personality traits and other individual-related factors have on the perceived usability were also examined.

In total, 2,239 Greek primary and secondary education teachers participated in the study through an online survey. The system usability scale (SUS) and Big 5 personality test questionnaires were adopted, as well as a demographics questionnaire and nine platforms were examined: e-me, eclass, Google Classroom, Microsoft Teams, Cisco Webex, Edmodo, Padlet, Skype and Zoom.

Most platforms were rated as satisfactory in terms of perceived usability as measured by SUS. SUS scores were not found to be significantly related with participants’ age, gender, private/public school, working relationship. Furthermore, openness to new experience and extraversion demonstrated the strongest positive correlation with perceived usability evaluation.

The current study used a sample of Greek teachers as participants, so the generalizability of results without considering cultural or organizational issues is of questionable validity. The Big 5 personality test is widely adopted; however, it seems that it does not capture comprehensively all possible dimensions of personality.

Acknowledging the correlations between personality traits and perceived usability for each platform, teachers may now choose the most user-friendly one depending on the personality traits. Designers can adapt their systems to meet users’ needs accordingly. Moreover, the reported results provide a frame of reference for the respective organizations and companies to compare the quality of user experience of their products and services. Thus, development costs of an e-learning platform/tool can be reduced accordingly.

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Perceived usability of a technological system affects the way users interact with it and consequently the whole learning experience. Thus, factors which may affect perceived usability and, in turn, the learning outcomes are of paramount importance and should be exhaustively examined. Giving that personality affects or is related to, other parameters related with technology (technology adoption, perceived and actual use, acceptance, interaction, perceived ease of use), this study addresses a significant research gap and sheds light to the before-mentioned issues.

The purpose of this study was to determine the impact of perceived usability and students' personality traits on their learning gain in an e-learning context at the university level.

The factors examined are related to individual characteristics such as students' personality traits, as well as to perceptual characteristics such as the perceived usability of the platform used. A total of 110 undergraduate students participated in the study. A one-group pretest-posttest research design was adopted. Big 5 personality test, System Usability Scale (SUS) and a general knowledge assessment questionnaire were used.

Perceived usability of Zoom platform is statistically significantly correlated with students' learning gain (r = 0.294, p = 0.002, s). Concerning learning effectiveness in the current e-learning scenario, students' final performance was found to be statistically significantly higher than the initial (p = 0.000, s). A hierarchical regression analysis (R² = 0.146) unveiled that Zoom's perceived usability and personality traits are significant predictors for learning gain (p = 0.011, s).

The findings of this research provide important implications regarding the design of lessons in an e-learning context.

A substantial fraction of the educational process is going online, especially in higher education. Thus, a thorough understanding of the factors which influence learning gain in an e-learning context is of significance.

The main contribution of this study is that it quantifies the variance of the learning gain explained by two factors, namely, SUS and personality.

The adverse effect of plastic pollution on the tourism industry is one of the emerging research areas in the field of sustainable tourism over the past years. However, there is a lack of discussion on this issue in the academic platforms. Considering this, in this chapter, a scientometric analysis of 110 academic publications from the Web of Science (WoS) between 1999 and 2021 related to plastic pollution and tourism is presented. A bibliometric analysis using CiteSpace was utilised to analyse the data to present the keyword timezone, collaboration network and co-citation network. The analysis shows that the publications in this field have increased rapidly, and it has become an emerging and interdisciplinary research topic. Scholars from Australia, Spain, Brazil and China have published most on the topic. The Chinese Academy of Science with four articles is the largest contributor in this field among other institutions. Moreover, citizen science is found to be a new keyword coming up in recent years, and human health is one of the major concerns. The findings from this study provide valuable insights for the academicians and policy makers in understanding the issue.