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This paper aims to focus on the application of multi-attribute decision-making methods (MADMs) to ascertain the optimal machining parameters while turning Ti-6Al-4V alloy under minimum quantity lubrication (MQL) conditions using Jatropha-curcas oil (JCO) bio-based lubricant.

The experiments were designed and performed using Taguchi L27 design of experiments methodology. A total of 27 experiments were performed under MQL conditions using textured carbide cutting tools on which different MADMs like Analytic hierarchy process (AHP), Technique for order preference by similarity to ideal solution (TOPSIS) and Simple additive weighting (SAW) were implemented in an empirical manner to extract optimize machining parameters for turning of Ti-6Al-4V alloy under set of constrained conditions.

The results evaluated through MADMs exhibit the optimized set of machining parameters (cutting speed V_c = 80 m/min, feed rate f = 0.05 mm/rev. and depth of cut a_p = 0.10 mm) for minimizing the average surface roughness (Ra), maximum flank wear (Vbmax), tangential cutting force (Fc) and cutting temperature (T). Further, analysis of variance (ANOVA) and traditional desirability function approach was applied and results of TOPSIS and SAW methods having optimal setting of parameters were compared as well as confirmation experiments were conducted to verify the results. A SEM analysis at lowest and highest cutting speeds was performed to investigate the tool wear patterns. At the highest speed, large cutting temperature generated, thereby resulted in chipping as well as notching and fracturing of the textured insert.

The research paper attempted in exploring the optimized machining parameters during turning of difficult-to-cut titanium alloy (Ti-6AL-4V) with textured carbide cutting tool under MQL environment through combined approach of MADMs techniques. Ti-6Al-4V alloy has been extensively used in important aerospace components like fuselage, hydraulic tubing, bulk head, wing spar, landing gear, as well as bio-medical applications.

This study examined the factors impeding the implementation of micro-credentials and accepting it as a credible source of earning professional qualifications and certifications necessary for pursuing higher education or other career goals.

The factors were identified by reflecting on the recent literature and Internet resources coupled with in-depth brainstorming with experts in the field of micro-credentials including educators, learners and employers. Two ranking methods, namely Preference Ranking for Organization Method for Enrichment Evaluation (PROMETHEE) and multi-objective optimization based on ratio analysis (MOORA), are used together to rank the major challenges.

The results of this study present that lack of clear definitions, ambiguous course descriptions, lack of accreditation and quality assurance, unclear remuneration policies, lack of coordination between learning hours and learning outcomes, the inadequate volume of learning, and lack of acceptance by individuals and organizations are the top-ranked and the most significant barriers in the implementation of micro-credentials.

The findings can be used by educational institutions, organizations and policymakers to better understand the issues and develop strategies to address them, making micro-credentials a more recognized form of education and qualifications.

The novelty of this study is to identify the primary factors influencing the implementation of micro-credentials from the educators', students' and employers' perspectives and to prioritize those using ranking methods such as PROMETHEE and MOORA.

The purpose of the study is to fabricate a joint between two aluminium metal matrix composites using microwave hybrid heating (MHH).

Taguchi design of experiments was applied to conduct the experimental study. The mechanical properties such as ultimate tensile strength, micro-hardness and porosity were studied. Grey Relational Analysis was applied to understand the significance of fabrication parameters of best performing sample. The dominant factor of fabrication was analysed using ANOVA. The best performance sample was further characterised using X-ray diffraction and field emission scanning electron microscopy. Energy dispersive X-ray was used to analyse the elemental composition of the sample.

The Aluminium Metal Matrix Composite (AMMC) joint was successfully fabricated using MHH. The mechanical properties were mainly influenced by the fabrication factor of exposure time.

The formation of AMMC joint using MHH might explore the way for the industries in the field of joining.

The purpose of this study is to develop a non-enzymatic based glucose-sensing platform composed of Bodipy-BBV dual system which can be monitored by a photodetector under the blue LED excitation.

The sensor has been developed from a dual system including a fluorescent dye, an aldehyde derivative of boron dipyrromethene (Bodipy) and a quencher, orto-boronic acid linked viologen (o-BBV) where their combination resulted in a ratiometric fluorescence quenching in ethanol: PBS (1:1, pH:7.4) solution under UV light excitation. By glucose addition, o-BBV has been released from the Bodipy and binded to cis-diol groups of glucose, thereby fluorescence emission of Bodipy has been regained. Furthermore, a setup consisting of a light emitting diode (LED) and a photodiode (PD) was used to prove electrical detection of glucose without the need for expensive and bulky optical equipment, enabling the development of a miniaturized and low-cost glucose-sensing platform.

The fluorescence intensity of the Bodipy derivative in the solution (2 × 10⁻⁶ M) was diminished by 93% in the presence of o-BBV solution (5 × 10⁻³ M). Upon the glucose addition, 81% of the Bodipy fluorescence intensity has been recovered after introduction of 30 mM of glucose, where the ratio of o-BBV/Bodipy was 35:1. A linear response between 10 and 30 mM glucose concentration was obtained, which covers the biologically significant range. A high correlation between the photodiode current and Bodipy fluorescence intensity was achieved.

Even though Bodipy molecules are known with their superior optical properties and applied to the fluorescence-based detection of glucose, to the best of the authors’ knowledge, no work has been reported on Bodipy-BBV dual system to detect glucose molecules as a non-enzymatic based method. This design enables the dye and the quencher to independently coexist in the solution, allowing for tuning of their individual concentrations to optimize the glucose sensitivity. Furthermore, an electrical light detection scheme consisting of a LED and a photodiode has been implemented to eliminate the bulky optical equipment from the measurement setup and further this work for the development of a compact and inexpensive sensor. The results presented here demonstrate the feasibility of this system for the development of a novel glucose sensor.

This study aims to investigate the relationship between dietary polyamine levels, metabolic risk parameters and anthropometric measurements in postmenopausal women.

This cross-sectional study was conducted with 562 45–64-year-old postmenopausal women who presented to a Family Health Center. To collect the data, the Descriptive Information Form and Food Frequency Questionnaire were used. In the data analysis, numbers, percentages, mean, standard deviation and multiple linear regression analysis were used.

The multiple linear regression analysis demonstrated that dietary putrescine intake was negatively associated with systolic blood pressure (ß = −0.179, p < 0.001), dietary spermidine intake was positively associated with waist circumference (WC) (ß = 0.142, p = 0.013), systolic blood pressure (ß = 0.188, p = 0.001), diastolic blood pressure (ß = 0.218, p < 0.001), body mass index (BMI) (ß = 0.169, p = 0.003) and waist-to-height ratio (WHtR) (ß = 0.156, p = 0.006), and dietary spermine intake was negatively associated with WC (ß = −0.158, p = 0.003), systolic blood pressure (ß = −0.195, p < 0.001), BMI (ß = −0.107, p = 0.042) and WHtR (ß = −0.138, p = 0.009).

Owing to the study’s cross-sectional nature, the lack of succession in the cause–effect relationship, the use of self-report Food Frequency Questionnaire to determine dietary polyamine intake and the inability to analyze seasonal differences are among the limitations of the study.

In this study, an association was determined between dietary polyamines, metabolic risk parameters and anthropometric measurements. The findings suggest that dietary polyamines in human health should be further investigated owing to the increasing metabolic risk parameters.

This study aims to identify and prioritize the key practices and strategies for effective global sourcing and supply chain management (SCM).

The study uses a combination of Pareto analysis and multi-objective optimization based on ratio analysis research methodology to analyze and establish the relationships among the identified key practices and strategies. Pareto analysis enables organization to prioritize organizational efforts and resources by focusing on the most critical factors.

The study shows that the “eco-friendly sourcing strategy”, “lean manufacturing” and “tool cost analysis” are the top critical practices and strategy variables for global sourcing and SCM, whereas the “risk management”, “procurement strategy” and “leverage digital solutions” are the critical practices and strategy variables.

The findings of this research can also assist organizations in making informed decisions to optimize their global sourcing and supply chain operations.

By using these methods, this research paper gives valuable insights into the critical practices and strategies that can enhance efficiency, mitigate risks and drive success in global sourcing and SCM. The subjects and elements this study identified will serve as a framework and suggestions for further theoretical investigation and real-world implementations.

The purpose of this paper is to provide a practical review of the use of the minimum quantity lubrication (MQL) system in turning operations, focussing on the application of the technique in the turning of different kind of materials.

The use of the MQL system was analysed by several researchers in the past years. Thus, in the present paper, a relevant sample of the main experimental studies that can be found in the literature was analysed to come up with a review with relevant information for researchers and industry.

The use of the MQL system can help to improve the outcomes of the turning process in several issues like surface quality or tool life. However, it was also recognised that in some cases, other cooling/lubricating methods can provide better results than the MQL system. Thus, the decision, whether to use or not the MQL system in a specific process, is of great importance.

The work is conveniently focussed to serve as a quick reference on the issue. At the same time, the work analysed the use of the turning of some of the main engineering materials that makes it useful for a wider range of researchers and metalworking firms. Finally, the review could be useful to improve the performance of the industry, especially for the metalworking firms in terms of costs, environmental impact and safety.

This study aims to examine the implementation of agile practices in Industry 4.0 to assess the financial performance measurements of manufacturing firms. It also investigates the relationship between supply chain performance and financial performance.

The study is based on an experimental research design by collecting data from 329 responses from key officials of manufacturing firms. The analyses are carried out to explore this modern concept with the help of the SPSS program, which is used to conduct a confirmatory factor and reliability analysis and Smart-partial least square (PLS) version 4.0 with structural equation modeling.

This research demonstrates the positive effect agile supply chain strategies in Industry 4.0 may have on manufacturing companies' financial performance as a whole. Everything throughout the supply chain in Industry 4.0, from the manufacturers to the end users, is taken into account as a potential performance booster. The values obtained from the model's study show that it is both dependable and effective, surpassing the threshold for such claims. The research is supported by factors like customer involvement (CUS), continuous improvement (CI), integration (INT), modularity (MOD), management style (MS) and supplier involvement (SI) but is undermined by factors including postponement (PPT).

According to the findings of the study, Industry 4.0 firms' financial performance and overall competitiveness are significantly improved when their supply chains are more agile. A more agile supply chain helps businesses to more rapidly adapt to shifts in consumer demand, shorten the amount of time it takes to produce a product, enhance product quality and boost customer happiness. As a consequence of this, there will be an increase in revenue, an improvement in profitability and continued sustainable growth.

There are literary works available on agile practices in various fields, but the current study outlines the need to understand how supply chains perform financially under the mediating effect of agile supply chains in Industry 4.0 which contribute most to the organization's success. The study will aid companies in understanding how agile practices will further the overall performance of the organization financially.

This study aims to investigate the effects of process input parameters (welding current, welding time, electrode pressure and holding time) on the output responses (nugget diameter, peak load and indentation) that control the mechanical properties and quality of the joints in dissimilar resistance spot welding (RSW) for the third generation of advanced high-strength steel (AHSS) quenching and partitioning (Q&P980) and (SPFC780Y) high-strength steel spot welds.

Design of experiment approach with two level factors and center points was adopted. Destructive peel and shear tensile strengths were used to measure the responses. The significant factors were determined using analysis of variance implemented by Minitab 18 software. Finally, multiresponse optimization was carried out using the desirability function analysis method.

Holding time was the most significant factor influencing nugget diameter, whereas welding current had the greatest impact on peak load and indentation. Multiresponse optimization revealed that the optimal settings were a welding current of 12.5 KA, welding time of 18 cycles, electrode pressure of 420 Kgf and holding time of 10 cycles. These settings produced a nugget diameter of 8.0 mm, a peak load of 35.15 KN and an indentation of 22.5%, with a composite desirability function of 0.764.

This study provides an effective approach for multiple response optimization to the mechanical behavior of RSW joints, even though there have been few studies on the third generation of AHSS joints and none on the dissimilar joints of the materials used in this study.

Cloud computing is relatively a new type of technology demanding a new method of management techniques to attain security and privacy leading to customer satisfaction regarding “Business Protection” measure. As cloud computing businesses are usually composed of multiple colocation sites/departments, the purpose of this paper is to propose a benchmark operation to measure and compare the overall integrated people-process-performance (PPP) among different departments within cloud computing organization. The purpose of this paper is to motivate staff/units to improve the process performance and meet the standards in a competitive approach among business units.

The research method was conducted at Cirrus Ltd, which is a cloud computing service provider where a focus group consists of six IT professionals/managers. The objective of the focus group was to investigate the proposed technique by selecting the best practices relevant criteria, with the relevant sub-criteria as a benchmarking performance tool to measure PPP via an analytic hierarchy processing (AHP) approach. The standard pairwise comparative AHP scale was used to measure the performance of three different teams defined as production team, user acceptance testing team and the development team.

Based on best practice performance measurement (reviewed in this paper) of cloud computing, the proposed AHP model was implemented in a local medium-sized cloud service provider named “Cirrus” with their single site data center. The actual criteria relevant to Cirrus was an adaptation of the “Best practice” described in the literature. The main reason for the adaptation of criteria was that the principle of PPP assumes multiple departments/datacenters located in a different geographical area in large service providers. As Cirrus is a type of SMEs, the adaptation of performance measurement was based on teams within the same data center location. Irrelevant of this adaptation, the objective of measuring vendors KPI using the AHP technique as a specific output of PPP is also a valid situation.

This study provides guidance for achieving cloud computing performance measurement using the AHP technique. Hence, the proposed technique is an integrated model to measure the PPP under monitored cloud environment.

The proposed technique measures and manages the performance of cloud service providers that also implicitly act as a catalyst to attain trust in such high information-sensitive environment leading to organizational effectiveness of managing cloud organizations.