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Development of non‐destructive methodology for detection of arc strike, spatter and fusion type of welding defects which may form on steam generator (SG) tubes that are in close proximity to the circumferential shell welds. Such defects, especially fusion‐type defects, are detrimental to the structural integrity of the SG. This paper aims to focus on this problem.

This paper presents a new methodology for non‐destructive detection of arc strike, spatter and fusion type of welding defects. This methodology uses remote field eddy current (RFEC) ultrasonic non‐destructive techniques and K‐means clustering.

Distinctly different RFEC signals have been observed for the three types of defects and this information has been effectively utilized for automated identification of weld fusion which produces two back‐wall echoes in ultrasonic A‐scan signals. The methodology can readily distinguish fusion‐type defect from arc strike and spatter type of defects.

The methodology is unique as there is no standard guideline for non‐destructive evaluation of peripheral tubes after shell welding to detect arc strike, spatter and fusion type of welding defects.

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.

Lean manufacturing (LM) concepts have been widely adopted in diverse industrial sectors. However, no literature review focusing on case studies describing LM implementation is available. Case studies represent the actual implementation and provide secondary data for further analysis. This study aims to review the same to understand the pathways of LM implementation. In addition, it aims to analyse other related review questions, such as how implementing LM impacts manufacturing capabilities and the maturity level of manufacturing organisations that implemented LM, to name a few.

A literature review of case studies that discuss the implementation of LM during the last decade (from 2010 to 2020) is carried out. These studies were synthesised, and content analyses were performed to reveal critical insights.

The implementation pattern of LM significantly varies across manufacturing organisations. The findings show simultaneous improvement in manufacturing capabilities. Towards the end of the last decade, organisations implemented LM with radio frequency identification, e-kanban, simulation, etc.

Reviewing the case studies documenting LM implementation to comprehend the various nuances is a novel attempt. Furthermore, potential future research directions are identified for advancing the research in the domain of LM.

This paper aims to clarify emerging aspects and trends of Six Sigma literature over 17 years, from 1992 to 2008.

The literature on Six Sigma from 417 referred journal articles in business and management disciplines, information systems and computer science, engineering, healthcare, etc. were systematically analyzed based on a scheme that consists of four distinct dimensions: publication year and journal, major themes, research type, and application sector (i.e. manufacturing vs service).

A number of key findings emerged: Six Sigma research is growing rapidly, covering various disciplines and domains with a great focus on Six Sigma tools and techniques; empirical research is dominant with more emphasis on case study approach; and the growing gap between manufacturing‐ and service‐focused articles implies the return of Six Sigma to manufacturing as its initial base. Although a large volume of literature is available on Six Sigma, the topic is still under development and offers potential opportunities for further research and applications.

The paper provides both academics and practitioners with a useful framework for pursuing rigorous Six Sigma research through explaining the chronological growth of Six Sigma, challenging themes of Six Sigma research, dominating research types and application areas in Six Sigma, and the major sources of Six Sigma information.

Detection of hidden defects of aluminum alloy plate with damping coating is a challenging problem. At present, only a few non-destructive testing methods exist to address this engineering problem. Without the restriction of skin effect, remote field eddy current (RFEC) overcomes the interference caused by the damping coating. The RFEC, which has potential advantages for detecting the hidden defects of aluminum plate with damping coating, can penetrate the metal plate to detect buried depth defects. This study aims to test how thick the RFEC sensor can penetrate the metal plate to detect the buried defects.

The magnetic field distribution characteristics are analyzed, the magnetic field intensity distribution is calculated, and the structure and parameters of the coil, magnetic circuit and shielding damping are determined through the two- and three-dimensional finite element simulation methods. Optimal excitation frequency is obtained, and the distance between the excitation coil and detection coil is determined by analyzing the relationship between excitation frequency and remote field points.

Simulation and experimental results verify the feasibility of applying the RFEC detection technology in detecting the hidden defects of aluminum alloy plate with damping coating.

In this paper, the RFEC testing model of hidden defects in aluminum plate sample with damping coating is established by using the finite element method.

This study aims to systematically review randomized clinical trials (RCTs) evaluated the effects of resveratrol on vascular flow-mediated dilation (FMD).

All published RCTs in English were systematically searched on PubMed and Scopus search engines up to October 2017. A total of 61 studies were found through search databases. The outcome variable of interest was FMD. Six articles which met inclusion criteria were included in this study.

From six studies, four showed a significant improvement in FMD after resveratrol supplementation acutely or chronically in subjects with cardio-metabolic risk factors. Two other studies did not show any significant effect of resveratrol on FMD.

The authors systematically reviewed the effectiveness of resveratrol supplementation on FMD for the first time. The findings suggest that pure resveratrol supplementation may have beneficial effects on endothelium dependent vasodilatation indicator, FMD.

The purpose of this paper is to capture the status of implementation of Six Sigma in various manufacturing industries and also examine the success of the Six Sigma by using different performance indicators.

The methodology of critical review involves the selection and classification of 112 research articles on the implementation of Six Sigma in different manufacturing industries. The selected articles are categorized by the following: articles distribution based on the year of publication, publication database, various journals, contribution of authors, continent, scale of industry, implemented approaches, focused industry, tools and techniques used in phases of Six Sigma methodology, and performance indicators used in Six Sigma implementation. Then after, future scopes of research opportunities are derived based on significant findings.

The literature revealed that: Very few work was undertaken on the implementation of Six Sigma in various manufacturing industries like ceramic, paper, gems and jewelry, cement, furniture, stone, fertilizer, forging, paper and surface treatment industries. Most of the researchers have considered very few performance indicators to identify the improvement after Six Sigma implementation. But, there is no clue regarding overall improvement in different perspectives after the implementation of Six Sigma. The financial indicators, personnel indicators, process indicators and customer indicators are useful to measure the overall improvement after the implementation of Six Sigma in the manufacturing sector.

The study was carried out on the implementation of Six Sigma methodology in various manufacturing industries, and various performance indicators were identified while implementing the Six Sigma methodology. Case studies pertaining to service industries were not covered here.

Very little research has been carried out to measure the overall success of implementing Six Sigma methodology in manufacturing industries. This paper will provide value to students, researchers and practitioners of Six Sigma by providing insight into the implementation of Six Sigma in manufacturing industries.

A major key success factor regarding proficient Bayes threshold denoising refers to noise variance estimation. This paper focuses on assessing different noise variance estimations in three Bayes threshold models on two different characteristic brain lesions/tumor magnetic resonance imaging (MRIs).

Here, three Bayes threshold denoising models based on different noise variance estimations under the stationary wavelet transforms (SWT) domain are mainly assessed, compared to state-of-the-art non-local means (NLMs). Each of those three models, namely D1, GB and DR models, respectively, depends on the most detail wavelet subband at the first resolution level, on the entirely global detail subbands and on the detail subband in each direction/resolution. Explicit and implicit denoising performance are consecutively assessed by threshold denoising and segmentation identification results.

Implicit performance assessment points the first–second best accuracy, 0.9181 and 0.9048 Dice similarity coefficient (Dice), sequentially yielded by GB and DR; reliability is indicated by 45.66% Dice dropping of DR, compared against 53.38, 61.03 and 35.48% of D1 GB and NLMs, when increasing 0.2 to 0.9 noise level on brain lesions MRI. For brain tumor MRI under 0.2 noise level, it denotes the best accuracy of 0.9592 Dice, resulted by DR; however, 8.09% Dice dropping of DR, relative to 6.72%, 8.85 and 39.36% of D1, GB and NLMs is denoted. The lowest explicit and implicit denoising performances of NLMs are obviously pointed.

A future improvement of denoising performance possibly refers to creating a semi-supervised denoising conjunction model. Such model utilizes the denoised MRIs, resulted by DR and D1 thresholding model as uncorrupted image version along with the noisy MRIs, representing corrupted version ones during autoencoder training phase, to reconstruct the original clean image.

This paper should be of interest to readers in the areas of technologies of computing and information science, including data science and applications, computational health informatics, especially applied as a decision support tool for medical image processing.

In most cases, DR and D1 provide the first–second best implicit performances in terms of accuracy and reliability on both simulated, low-detail small-size region-of-interest (ROI) brain lesions and realistic, high-detail large-size ROI brain tumor MRIs.

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.

Aerospace and defence industries use the materials having better properties at elevated temperatures, and Inconel 718 is one of that. The complexity in realizing complex and intricate shapes necessitate the product realization through additive manufacturing. This paper aims to investigate the wear behaviour of additive manufactured material.

The wear behaviour of additively manufactured Inconel 718 samples through direct metal laser sintering process at three different build orientations was experimentally investigated using a standard pin-on-disc wear tester.

Among the varied wear parameters, the load was identified as the most influencing parameter on the wear rate. In addition, the post-failure analysis of the worn surface of the pins under the scanning electron microscopy revealed the presence of various wear mechanisms.

Almost, the industries are now focussed on their production through additive manufacturing owing to its advantages. The present work displays the wear behaviour of the additive manufactured Inconel 718 and its associated wear mechanisms.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-08-2019-0322.