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The Air Pollution Tolerance Index (APTI) and Anticipated Performance Index (API) of Azadirachta indica, Ficus benghalensis, and Ficus religiosa were compared to assess their tolerance to air pollution in different environmental setups. The study was conducted at six different locations with different environmental setups, including Urban, Industrial, Institutional and Agricultural. The parameters used for APTI were pH, relative water content, total chlorophyll content, and ascorbic acid content in the leaves, while API was calculated using APTI along with the socio-economic characteristics of the targeted species. Three species were selected, with nine replicates of each species from each setup (i.e., 6×9×3, which means a total of 162 samples) were analyzed for APTI during the winter season, when there is a lower mixing height that prevents the dispersion of pollutants and makes the environment highly polluted, and trees show high tolerance in a polluted environment. The APTI values of all the targeted species were higher in industrial setups than in the other environmental setups, i.e., 20.42 ± 1.65 for A. indica, 14.75 ± 0.53 for F. benghalensis, and 13.39 ± 1.11 for F. religiosa. The sample t-test showed a significant difference in the APTI of the industrial setup and other setups (p=0.0000). A. indica was found to be a tolerant species, and F. benghalensis and F. religiosa were intermediate-tolerant species based on APTI. F. benghalensis and F. religiosa fall under the excellent and A. indica falls under the very good category based on API. Based on these two indices, the best tree species were identified for plantation and the abatement of air pollution in industrial areas.

This study aims to create a performance evaluation model for the food processing machinery industry. The goal is to help food processing plants improve both process quality and competitiveness. Additionally, component failures may disrupt the continuous operation of the food processing machine, potentially resulting in insufficient production and delays in delivery, which in turn leads to cost losses. For the sold food processing machinery, decreases in the average number of failures within a unit of time, the average repair response time when a failure occurs, and the average repair duration are three crucial factors in minimizing the total expected loss due to machine failures. Based on these three important factors, this study established the following evaluation indices: (1) the processing performance index, (2) the repair reporting performance index, and (3) the maintenance performance index. These indices serve as tools for assessing the performance of the three key operational aspects. This study employed a radar chart to construct the evaluation model, which can directly compare the critical values with the point estimates of three indices. Consequently, this approach can judge whether the operational performance has achieved the required level. This can maintain the simplicity and usability of point estimates while reducing the risk of misjudgment due to sampling errors.

Supply chain management (SCM) has gradually evolved beyond the straightforward logic of benefits and economic viewpoints. Supplier selection and performance evaluation are the crucial strategic components of any SCM system with a substantial economic impact and risk reduction. Several conflicting factors make supplier selection a challenging multi-criteria decision-making problem. This paper introduces a method called alternative ranking with the elected nominee (ARWEN) to select suppliers in Iran’s dairy product chain store. The primary principle of ARWEN is to choose the best alternative based on the lowest change rate rather than the elected nominee. Four extensions of the ARWEN method are proposed depending upon the nature and level of information available to the decision-makers. A fifth extended version termed E-ARWEN is also recommended to consider the negative form of the elected nominee. Two novel statistical tools, the ranking performance index and the Zakeri-Konstantas distance product correlation coefficient, are also put forth to validate the ARWEN extensions’ outcomes. The results and verification of this new method are carried out through two supplier selection case examples. Comprehensive comparisons were carried out to explore the new methods’ behaviors, indicating ARWEN III and E-ARWEN have similar behavior to VIKOR, SAW, and EDAS in generating rankings.

Purpose The purpose of this paper is to improve autonomous flight performance of an unmanned aerial vehicle (UAV) having actively sweep angle morphing wing using simultaneous UAV and flight control system (FCS) design. Design/methodology/approach An UAV is remanufactured in the ISTE Unmanned Aerial Vehicle Laboratory. Its wing sweep angle can vary actively during flight. FCS parameters and wing sweep angle are simultaneously designed to optimize autonomous flight performance index using a stochastic optimization method called as simultaneous perturbation stochastic approximation (SPSA). Results obtained are applied for flight simulations. Findings Using simultaneous design process of an UAV having actively sweep angle morphing wing and FCS design, autonomous flight performance index is maximized. Research limitations/implications Authorization of Directorate General of Civil Aviation in Turkey is crucial for real-time UAV flights. Practical implications Simultaneous UAV having actively sweep angle morphing wing and FCS design process is so beneficial for recovering UAV autonomous flight performance index. Social implications Simultaneous UAV having actively sweep angle morphing wing and FCS design process achieves confidence, high autonomous performance index and simple service demands of UAV operators. Originality/value Composing a novel approach to improve autonomous flight performance index (e.g. less settling and rise time, less overshoot meanwhile trajectory tracking) of an UAV and creating an original procedure carrying out simultaneous UAV having actively sweep angle morphing wing and FCS design idea.

The calcium carbonate whisker (CW) and basalt fiber are gaining popularity due to its enhanced mechanical properties in composites. Also, the short and long fibers provide bridging role and resistance against cracking from micro- to macro-scale, respectively. The usage of long and short hybrid basalt fiber along with addition of CW in cement-based composites is still a research gap. In this work, experimental behavior of CW basalt hybrid fiber reinforced mortar is considered with various content and length (3 mm, 6 mm, 12 mm, and 20 mm) of hybrid basalt fibers. In addition to this, synergy performance index is determined to quantitatively evaluate the positive interaction of hybrid basalt fiber in cementitious materials. The strengthening effect of whiskers and basalt fibers are also studied using scanning electron microscopy. The CW with various basalt fiber contents having different length of hybrid basalt fiber is used. It was found that the four various length of hybrid basalt fiber together with CW in cement mortar exhibited enhanced compressive, flexural, and split tensile strength than that of pure mortar and single length basalt fiber reinforced cementitious mortar. The results of synergy performance index showed similar trend with the experimental results. The strengthening effect caused by step by step crack arresting mechanism was also observed in cementitious material.

In this paper, we propose a general class of indices that can be used for comparing the performances of organizations providing a given public service to citizens, such as universities, hospitals, nursing homes, employment agencies or other institutions. In particular, we handle the case where evaluation is performed by assessing the probability that a given event has happened as a result of the service provided to users requiring it. Indices are designed for settings where users can be divided into groups with similar characteristics in order to account for case-mix, that is, for the different composition of users within each organization with respect to personal features influencing the probability of the event at hand. For the proposed class, we build a taxonomy leading to nine index types. These different types constitute a useful toolbox to satisfy specific needs and/or criteria set by the evaluator in applied contexts. A general inferential framework is also discussed to deal with settings where, whatever the index chosen, its value has to be estimated from sample data. A simulation study based on a real-world dataset is presented to assess the behavior of indices’ estimators.

Verification and validation of product quality highly affects the success of product design and manufacturing processes as well as the long-term collaboration between buyers and suppliers. Lifetime testing for acceptance is the main bottleneck in verification and validation and often requires considerable time and expense, especially in the current high-product-yield era. To establish a cost-effective and risk-controllable life testing sampling scheme, we propose a variables-type multiple-dependent-state (MDS) sampling plan using the lifetime performance index under a Weibull distribution with Type-II right censoring. The design parameters of the lifetime-capable MDS sampling plan are formulated as optimization models to minimize the required number of testing failures subject to nonlinear constraints for the desired lifetime capability levels and allowable risks regulated by the supplier and buyer. Compared with variable single sampling plans, the plan proposed herein is more cost-effective sampling and has greater discriminatory power. The applicability of the proposed plan is demonstrated through an example.

PurposeThe purpose of this study is to explore the potential for the development of a country logistics performance assessment approach based upon textual big data analytics.Design/methodology/approachThe study employs design science principles. Data were collected using the Global Perspectives text corpus that describes the logistics systems of 20 countries from 2006–2014. The extracted texts were processed and analysed using text analytic techniques, and domain experts were employed for training and developing the approach.FindingsThe developed approach is able to generate results in the form of logistics performance assessments. It contributes towards the development of more informed weights of the different country logistics performance categories. That said, a larger text corpus and iterative classifier training is required to produce a more robust approach for benchmarking and ranking.Practical implicationsWhen successfully developed and implemented, the developed approach can be used by managers and government bodies, such as the World Bank and its stakeholders, to complement the Logistics Performance Index (LPI).Originality/valueA new and unconventional approach for logistics system performance assessment is explored. A new potential for textual big data analytic applications in supply chain management is demonstrated. A contribution to performance management in operations and supply chain management is made by demonstrating how domain-specific text corpora can be transformed into an important source of performance information.

In highly-competitive markets, product quality is a critical element of sustainable development for manufacturing enterprises. The pursuit of quality is in essence a commitment to meeting the needs and expectations of customers. Firms often express customer needs in terms of quality characteristics in order to evaluate, monitor, and improve process performance. Reliability is an important quality characteristic. Specifically, reliability is the probability that a product will function as intended and will not malfunction within a certain period of time under certain operating conditions. Clearly, reliability influences the final evaluation made by customers of product quality. Since reliability is a time-oriented quality characteristic, it follows an exponential distribution. The performance standard for most quality indices is 1. To bring evaluation of reliability in line with convention, we propose ratio-based lifetime performance index (RLPI) θL. However, time-oriented data are continuous random variables, which implies that the observed values of the data are not precise. Furthermore, the performance of a product in various aspects inevitably declines over time. Clearly, longer product lifetime is not always better; it depends on the type of product. We therefore propose a two-tailed fuzzy statistical test for the RLPI θL to assist manufacturing enterprises in making more accurate evaluations of product reliability. An illustrative example is presented to demonstrate the practical applicability of our proposed approach.

Sustainable Development Goal 9 targets (SDG 9 targets) are mainly tracked through the indicators of penetration of internet and mobile broadband subscription, logistic performance index, quality and ranking of the universities, investment in research and development initiatives, industrial reforms and emission control, and connectivity to rural areas. The attainment of many of these targets and tracking of indicators is confronted by challenges of poor awareness, funding issues, distorted policies, and implementation failures. This systematic review on achievements, challenges, and future scope in attaining SDG 9 consolidates the literature from the Web of Science, related to SDG 9 and indicators, since 2017; develops bibliometric patterns; conducts thematic analysis by focusing the leading indicators of SDG 9; and develops agenda for future research. The major limitations of this study include focusing on selected indicators and limited literature availability. This review recommends policymakers, researchers, and administrators to focus on promising themes such as tackling the digital divide and ensuring digital justice and digital equality; clean fuel and technology adoption; enhancing internet and mobile broadband subscription with reduced negative impacts, logistic sector reforms; industrial policy reforms and technology integration; improving the quality and sustainability of universities; and increasing funding and support for research and development initiatives and improving the rural connectivity.