Current Industry Practice Research Articles

Blinding Protocols for Acquisition of Potentially Sensitive Food Safety Information

Difficulties associated with addressing research problems can revolve around the collection of data from private entities. Potential issues can arise when collecting food samples or food safety data from industry or third-party sources because of concerns about distribution or exposure of potentially sensitive information. Industry is cautious of its involvement in research projects because issues associated with production levels, capital investment, regulatory inquiries, unwarranted publicity, or other legal aspects can arise depending on the nature of information gathered, and information may be inadvertently released into the public domain. Well-designed clinical trials with animals or humans use blinding methods to reduce bias. In this study, a similar strategy was applied to acquisition of sensitive data to gather meaningful food safety related data while assuring that information provided was not at risk. Blinding methods for collecting electronic data and material samples were created to obtain materials and records directly from participating frozen food companies. This approach provided insight into current industry practices without potential downsides for participating companies. Analysis of food safety concerns using industry data and the distribution of findings can be of assistance industry-wide for conducting risk assessments and developing improved research-based food safety plans. The method described was designed to collect information using blinding protocols to reduce bias and prevent traceback to the original source. The use of blinding protocols promotes industry participation and creates data collection with anonymity for the original source, which can improve reliability of the research and applicability for industry. These blinding protocols are suitable for use in future food safety research projects involving data within and between various segments of the food industry and could be used to encourage collection of valuable industry samples and data.

Improvement of Cultivation Quality of Future Environmental Protection Talents: from Scientific Literacy Aspects

In recent years, as the development of environment science, new demands are needed for the cultivation of environmental protection talents. The improvement of scientific literacy has become an urgent need in the cultivation of undergraduate students major in environmental science and engineering. A good talent training model can promote the output of environmental protection talents and support the future environmental construction. In this paper, authors introduced the settings and practice of “Environmental Microbiology Practice” (EMP) in Miami College of Henan University. The teaching group of Miami College believed that EMP is the most suitable teaching link to help undergraduates understand the frontiers of the subject and improve scientific research thinking and did a series of reforms on the EMP course around (1) Current microbiological industry practice; (2) Frontier expansion of environmental microbiology; (3) Cultivation of scientific literacy. Combined with the students’ achievements and a questionnaire, the effectiveness of EMP has also been analyzed. By analyzing the practice of EMP in Miami College, this study provided an effective way for the improvement of scientific literacy and quality of undergraduate students. This cultivation idea and method is also of great significance for the cultivation of reserve talents of environmental protection who meet the needs of environmental scientific research and environmental protection in the new era.

Reliability and applications of a new design method for calculating hot-spot stress in CHS double K-joints under arbitrary combined loading

This paper presents further development of a simple and accurate new method for calculating hot-spot stress in circular hollow section (CHS) double K (DKK) joints to enable safe application for practical design. Such joints are widely used in the construction of offshore wind turbine (OWT) jackets and use of this design approach offers the opportunity to reduce the weight of these structures. The new hot-spot stress calculation method decomposes any arbitrary brace load combination (axial load, in-plane bending, out-of-plane bending) into six basic load cases and employs only 11 key stress concentration factors (SCFs) to define stress distributions around the weld toes of all four brace-chord connections in the DKK joint. This paper applies the UK Department of Energy (UK DEn) criteria for acceptance to ensure that the new method is safe. This design method is then applied to design two representative jacket structures in the North Sea (Seagreen and East Anglia wind farms) and the structures are compared to those designed using the current industry practice of calculating hot-spot stress. This comparative study indicates that steel weight savings of 10.43% and 7.07% may be achieved using the new hot-spot stress calculation method whilst achieving the same predicted service life.

Towards a continuous certification of safety-critical avionics software

Many industries use safety-critical systems and software, the failure of which may result in the loss of human lives. This article investigates the development and certification of safety-critical software, with a focus on the avionics industry. It highlights the problems encountered in companies to demonstrate compliance with the certification requirements and indicates current industrial practices. It demonstrates the interest and importance of closely and continuously integrating certification requirements in the software development process. It underlines a very recent trend in industry that consists in taking inspiration from agile principles in order to ensure that certification requirements applicable to software development are met as early as possible. It presents some successful industrial experiments and concludes on practical lessons that could be transferred to other projects.

“Talking a different Language”: Anticipating adversary attack cost for cyber risk assessment

Typical cyber security risk assessment methods focus on the system under consideration, its vulnerabilities, and the resulting impact in the event of a system compromise. Cyber security, however, increasingly requires anticipating the moves of intelligent adversaries, who make decisions based on a range of factors including the cost of their attacks. A study of current risk assessment literature and industry practice shows that consideration of this cost is a notable gap in the understanding of adversaries. The factors of cost experienced by an adversary are established in this paper as Time, Finance, and Risk, supported by a practical study undertaken with relevant security practitioners. Using these factors as a base, a framework is proposed and developed to support the probabilistic determination of cost incurred by an adversary. This framework is an important extension to existing cyber security risk assessments, and is demonstrated in the paper through the use of a case study.

Estimating porosity and permeability in the Springbok Sandstone, Surat Basin (Queensland), using new wireline log-based workflow

The Upper Jurassic Walloon Coal Measures of the Surat Basin (Queensland) host some of the most prominent coal seam gas (CSG) resources in Australia. The Walloon Coal Measures are directly overlain by the Springbok Sandstone formation, historically referred to as a regional aquifer. An increasing number of studies and industry models suggest relatively limited hydraulic connectivity within the formation and between it and the underlying coal measures, due to extreme lithological heterogeneity. Accurate evaluation of the permeability, as well as lateral and vertical continuity of the lithological units within the Springbok Sandstone, is critical in reservoir models that form the basis of reasonable aquifer protection practices and impact prediction. This study presents a wireline log-based workflow applied to identify permeable zones within the Springbok Sandstone in 31 CSG wells across the Surat Basin that allows robust estimations of porosities and Klinkenberg permeabilities. The workflow primarily utilises spontaneous potential, density, neutron and resistivity logs, and was developed by integrating current industry practices implemented by operators on a local scale to identify risk (permeable) zones in the vicinity of targeted coal seams. The results of this case study indicate that permeable zones within the interval are volumetrically minor (on average 25% N/G) and likely isolated, with Klinkenberg permeabilities rarely exceeding 10–20mD. This evidence for low hydraulic connectivity, as well as significant local variations in the character of the Springbok Sandstone, suggests that the definition of the formation as a regional, continuous aquifer and the way it is modelled needs to be revised.

Fixing Design Inconsistencies of Polymorphic Methods using Swarm Intelligence

Background: Modern industry is heavily dependent on software. The complexity of designing and developing software is a serious engineering issue. With the growing size of software systems and increase in complexity, inconsistencies arise in software design and intelligent techniques are required to detect and fix inconsistencies. Aim: Current industrial practice of manually detecting inconsistencies is time consuming, error prone and incomplete. Inconsistencies arising as a result of polymorphic object interactions are hard to trace. We propose an approach to detect and fix inconsistencies in polymorphic method invocations in sequence models. Method: A novel intelligent approach based on self regulating particle swarm optimization to solve the inconsistency during software system design is presented. Inconsistency handling is modelled as an optimization problem that uses a maximizing fitness function. The proposed approach also identifies the changes required in the design diagrams to fix the inconsistencies. Result: The method is evaluated on different software design models involving static and dynamic polymorphism and inconsistencies are detected and resolved. Conclusion: Ensuring consistency of design is highly essential to develop quality software and solves a major design issue for practitioners. In addition, our approach helps to reduce the time and cost of developing software.

NEXUS FRAMEWORK FOR WHOLE-CORE FUEL PERFORMANCE: CURRENT APPLICATIONS AND FUTURE TRENDS

Current industry practice in fuel licensing often relies on thermo-mechanical modeling of a fuel rod with an artificially constructed bounding power history. The benefit of this approach is that it is computationally efficient; however, the drawbacks are that 1) such an approach is not always conservative, for instance when modelling phenomena related to late onset pellet-clad gap closure; and 2) it can poorly estimate available safety margins for fuel operating at high local power densities and/or to high burnup. For these reasons NNL developed an in-house whole-core fuel performance framework – NEXUS – to enable modelling of all fuel rods in the core using the ENIGMA fuel performance code and computed power histories from core simulation packages (currently limited to PARCS or SIMULATE). One of the main objectives was to create a tool that was both computationally efficient and user friendly. The former was achieved by making use of parallelisable architecture, while the latter was achieved by minimising necessary user input and providing tools for easy interrogation of the fuel performance output. NEXUS has been applied to several LWR operational scenarios, which we summarise in this paper, including steady-state operation of an ABWR, and a rod ejection accident in a small modular soluble boron free PWR and a GWe-class PWR. We also summarise current development activities related to integrating NNL’s in-house fuel performance Monte Carlo uncertainty analysis software CASINO into the NEXUS framework.

Product line selection of fast-moving consumer goods

The fast-moving consumer goods sector relies on economies of scale. However, its assortments have been overextended as a means of market share appropriation and top-line growth. This paper studies the selection of the optimal set of products for fast-moving consumer goods producers to offer, as there is no previous model for product line selection that satisfies the requirements of the sector. Our mixed-integer programming model combines a multi-category attraction model with a capacitated lot-sizing problem, shared setups and safety stock. The multi-category attraction model predicts how the demand for each product responds to changes within the assortment. The capacitated lot-sizing problem allows us to account for the indirect production costs associated with different assortments. As seasonality is prevalent in consumer goods sales, the production plan optimally weights the trade-off between stocking finished goods from a long run with performing shorter runs with additional setups. Finally, the safety stock extension addresses the effect of the demand uncertainty associated with each assortment. With the computational experiments, we assess the value of our approach using data based on a real case. Our findings suggest that the benefits of a tailored approach are at their highest in scenarios typical fast-moving consumer goods industry: when capacity is tight, demand exhibits seasonal patterns and high service levels are required. This also occurs when the firm has a strong competitive position and consumer price-sensitivity is low. By testing the approach in two real-world instances, we show that this decision should not be made based on the current myopic industry practices. Lastly, our approach obtains profits of up to 9.4% higher than the current state-of-the-art models for product line selection.

Toward Programmable DOCSIS 4.0 Networks: Adaptive Modulation in OFDM Channels

The sixth generation of DOCSIS standard is currently under development for the provisioning of multi-Gbps services over cable networks. Building upon DOCSIS 3.1 (D3.1), DOCSIS 4.0 (D4) introduces several features including full-duplex transmission and extended-spectrum, which benefit from subcarrier-level OFDM modulation configurations to adapt to varying channel conditions. To exploit the full potential of D4, we propose a softwarized adaptive subcarrier modulation management framework. The optimization system consists of (i) a clustering mechanism that classifies CMs (Cable Modems) with a similar channel condition into the same group using a sparsified K-means algorithm and (ii) an efficient profile generation mechanism to balance achieved channel throughput and packet error rate within the same group. Then, we implement key elements of the softwarized system using a virtualized network function in our DOCSIS experimental testbed that enables the programmatic control of OFDM channels using D4 performance parameters. Our experimental results show that the proposed optimization function offers significant improvements in OFDM channel throughput over current industry management practices. Furthermore, we confirm via simulations that using a novel clustering algorithm for the classification of CM populations and a new bit-loading method measurably enhances channel performance in large-scale distributed deployment scenarios.

CHARACTERIZATION OF AEROGEL BASED THERMAL INSULATION BLANKETS, ECONOMICS, AND APPLICATIONS FOR DOMESTIC WATER HEATERS

One of the main ways to improve the performance of thermal systems is using better thermal insulation. Recent developments of high performance thermal insulation introduced thermal insulation blankets for low and moderately high temperature applications. One of the leading insulation technologies are aerogel based insulation blankets. Before studying the performance of thermal systems insulated with these materials, it is important to characterize these blankets under conditions similar to the operating conditions. In this study, thermal conductivity measurement experiments are conducted on Low Temperature High Performance Insulation (LTHPI) and High Temperature High Performance Insulation (HTHPI) blankets and their results were discussed. Tests also conducted are scanning-electron-microscope (SEM) imaging to better understand the nano-structure and thermal conductivity test. Results in this paper show SEM images for Aspen®’s Spaceloft® and Pyrogel® XT-E blankets, and X-ray imaging showing the components inside the blankets’ aerogel to be Silicon, Oxygen, and Carbon. Thermal conductivity measurements were conducted for both LTHPI and LTHPI insulation materials. The thermal conductivity results confirm the results mentioned in the literature, showing that the thermal conductivity is 0.0159 W / (m.K) for LTHPI and 0.0188 W / (m.K) for HTHPI at 25 oC. It can be said that the tested blankets show a promising performance in thermal systems. This paper also demonstrates a comparison of utilizing high performance thermal insulation with current industry practice in domestic water heaters, and a discussion on its economic impacts for individual and national levels. This discussion shows that a minimum of 3.7 billion USA dollars can be saved annually by adjusting regulations to enforce water heater manufacturers to use HPI in their products.

Errors in microseismic events locations introduced by neglecting anisotropy during velocity model calibration in downhole monitoring

Microseismic monitoring is the only tool to provide locations of microseismic events induced e.g. during hydraulic fracturing of unconventional reservoirs. Obtained locations become a baseline for the evaluation of stimulation effectiveness. However, due to several factors, they can be different from the true ones and lead to misinterpretation. Most important is the inaccuracy of the velocity model used in the location procedure, which is often amplified by seismic anisotropy. Even though the anisotropy is a common feature of organic-rich mudrocks, it is often neglected in the current industry practice. The usual approach is to produce a set of isotropic models, valid for the limited subsurface area only, which compensate for anisotropy effects. Here we explore how the accuracy of microseismic events' locations is affected when neglecting the anisotropy during velocity model building using traveltimes of calibration shots. We analyse events' mislocations using the synthetic modelling that simulates an ongoing multi-stage treatment in a vertically-transverse isotropic (VTI) media, monitored with a single vertical borehole. Finally, we provide a quantitative interpretation of location errors expected to be present when VTI anisotropy is being neglected. The most important result is the demonstration of how spatially limited are single-stage isotropic models in terms of correct event locations, despite performing an accurate calibration. Also, we show the limited gain in terms of location accuracy when multi-stage isotropic velocity models are constructed. As the ultimate solution to reduce location errors, we propose to account for anisotropy by inverting VTI anisotropy model parameters even when only part of calibration data is available.

Bayesian cross-product quality control via transfer learning

ABSTRACT Quality control is essential for modern business success. The traditional statistical process control (SPC), however, lacks efficacy in current high-variety low-volume industrial practices since the historical reference data in Phase I are usually too scarce to infer the in-control process parameters accurately. To solve this ‘small data’ challenge, a novel Bayesian process monitoring scheme via transfer learning is proposed to facilitate a cross-product data sharing. In particular, a joint prior distribution is taken to explicitly capture the relatedness between the process data of two similar products, through which the process information can be transferred from one product (source domain) to improve the Bayesian inference for the other product (target domain). The posteriors can be derived analytically in closed forms by using generalised hypergeometric functions, thereby leading to a computationally efficient control chart for the online real-time monitoring in Phase II. A user-specified parameter is also provided to enable a better theoretical understanding of the transferability matter and a free practical control of the transferred information across domains. Extensive numerical simulations and real example studies of an assembly process validate the superiority of our proposed scheme in terms of both the false alarm rate and detection capability.

Nanohydroxyapatite (n-HAp) as a pickering stabilizer in oil-in-water (O/W) emulsions: a stability study

Surfactant-free emulsions, such as Pickering emulsions, have been gaining an increased interest. They constitute green alternatives to the current industrial practices in emulsion technology finding diverse technological uses. In this work, nano-hydroxyapatite (n-HAp) was tested as an oil-in-water (O/W) Pickering stabilizer using a chemical system comprising sunflower oil at different O/W ratios (10/90 to 60/40) and n-HAp at concentrations ranging from 0.5 to 15 wt%. The produced emulsions were characterized, and stability evaluated over a two-month period. Based on the results achieved for the 20/80 series, a model to predict the emulsion stability taking into account the O/W ratio, total solids content, droplet diameter, and n-HAp dimensions, was developed. Cryo-SEM evidenced the attachment of n-HAp particles at the oil surface (oil core-n-HAp shell morphology), corroborating their role as Pickering stabilizers. The experimental results, versus the predicted results were compared using a ternary phase diagram, which evidenced the formation of three zones (unstable, stable and gel) depending on the used O/W ratio and n-HAp concentration. Moreover, the comparison of the predicted with the obtained experimental data validated the model predictability.

Managing carbon footprint for a sustainable supply chain: a systematic literature review

PurposeThe carbon emissions due to industrial production and market consumption activities are the major contributors to global warming. With the signing of UN Paris Accord 2016 on climate change, the world's major countries are devising measures to combat climate change and attain a sustainable, low-carbon future. Globalization demands companies not only to adopt greener manufacturing practices internally for reduced carbon footprint (CFP) but beyond its boundaries (i.e. its supply chain). This study aims to discuss the relationship between CFP and sustainable supply chain, as evident in the current literature and industry practices. It provides a total comprehension of past, present and future headings in the CFP area and its contribution to a sustainable supply chain.Design/methodology/approachA systematic literature review and analysis have been undertaken in supply chain sustainability and CFP. A bibliometric approach is adopted for this investigation, and one of the biggest computerized databases, “Scopus,” has been picked. In total, 37 articles have been zeroed in after a careful and watchful screening of firmly related topics.FindingsMost researchers gave predominance to environmental impact among the three pillars of sustainability (economy, society and the environment) for a sustainable supply chain environment. Only a few researchers were motivated to cover social development and social responsibility aspects. This review highlights how managing a CFP is one of the significant attributes of sustainable development. Existing literature in the field of CFP and sustainability have been written on actual industry cases. Food, electricity and energy are some significant industries where supply chain sustainability successfully reduces carbon emission.Originality/valueThe theory-building strategy with recommendations on the conceptualization of a sustainable supply chain is limited in the literature. This study gives broad ideas on how organizations modified and redeveloped different tools and technologies to make their supply chain more sustainable. The strategic role of different carbon policies, environmental rules and regulations in the domain of CFP is also recognized in this work. This study highlights the biases of most of the researches toward applications than policy interventions. This study discusses the theoretical perspective about how CFP affects supply chain management and helps organizations and researchers develop a new set of approaches in handling CFP and other sustainability aspects.

New rational test for reinforced-concrete pipe eliminating subjective crack-width criteria

This study proposes a new robust and rational test method for reinforced concrete pipe (RCP), which neither requires additional costly equipment, nor disrupts current industry practice. The current century old Three-Edge Bearing Test (TEBT), which is the most widely used worldwide, is operator sensitive and does not work well for emerging lined pipes. It relies on the skill and experience of the operator for capturing the occurrence of a 0.3 mm wide crack using a leaf-gauge, which induces subjectivity and error. TEBT was modified by eliminating visual crack width monitoring and adopting rational instrumentation. A wide range of full-scale RCP specimens with various diameters and single, double and triple reinforcing steel cage configurations were instrumented and subjected to the modified TEBT to obtain load vs. deflection curves. Traditional 0.3-mm visual crack readings were also taken for comparison. It was concluded that the new test method could determine the D-load while eliminating the uncertainty associated with visual crack detection. The new modified test method could also capture true structural behavior of the RCP, thus better reflecting the RCP reinforcing steel-cage design.

Life cycle assessment for enhanced Re-liquefaction systems applied to LNG carriers; effectiveness of partial Re-liquefaction system

The marine industry has been striving to seek for proper strategies to curb air emissions from global shipping activities. To support the transition to sustainable shipping, this paper was proposed to evaluate the holistic environmental benefits of the LNG partial re-liquefaction system applied to LNG carriers by comparing among five different combination/configuration of LNG re-liquefaction systems. The theory of life cycle assessment was employed with the help of a commercial software, Sphera GaBi version 2019 to quantify the magnitude of various emissions under different life stages of the proposed systems: manufacturing, installation, use and recycling. A case study was implemented with a 174,200 m3 LNG carrier and the input data for the analysis was collected from true-to-life sources provided by manufacturers and ship operators. The electric consumption of the five systems were calculated by means of Aspen HYSYS software. A range from 1.23 to 1.64 kWh/kg was estimated and was used as key parameters to confirm the onboard electricity demands at the use phase of the five systems. The results revealed that the partial re-liquefaction system had considerable effects on the reduction in emission levels across the following five impact categories: Global Warming Potential, Particulate Matter, Photochemical Ozone Creation Potential, Eutrophication Potential and Acidification Potential. An optimal option which adopted the partial re-liquefaction system was found to release 4.49 × 108 kg CO2 eq. 1.25 × 106 kg PM2.5 eq. 7.16 × 106 kg NMVOC eq. 2.46 × 106 kg N eq. and 1.13 × 107 kg SO2 eq. in its lifetime, which were roughly equivalent to 25% emission reductions compared to the rest of the candidates to which the partial re-liquefaction principle was not applied. Lastly, it clearly presents the effectiveness of life cycle assessment. This research, particularly, suggests that this holistic approach should not be underused for resolving innumerable maritime environmental issues that appear unsolvable with the current practices in the maritime industry.

Online Evaluation for the Accuracy of Electronic Voltage Transformer Based on Recursive Principal Components Analysis

The electronic voltage transformer (EVT) has received much attention with the recent global trend to establish smart grids and digital substations. One of the main issues of the EVT is the deterioration of its performance with long-term operation which affects the control and protection systems it is employed for and hence the overall reliability of the power grids. This calls for the essential need for a reliable technique to regularly assess the accuracy of operating EVT in real-time. Unfortunately, traditional calibration methods cannot detect the incipient EVT performance change in real-time. As such, this paper presents a new online method to evaluate the accuracy of the EVT. In this regard, the Q-statistic is calculated based on the recursive principal components analysis (RPCA) using the output data of EVT to map up the changes of metering error on the electric–physics relationship. By employing the output data of the EVT along with the power grid characteristics, the performance of the EVT is evaluated without the need for a standard transformer, as per the current industry practice. Results show that the proposed method can assess the EVT with a 0.2 accuracy class.

Teacher industry placement in Australia: Voices from vocational education and training managers

An important aspect of vocational education and training (VET) teaching is education that is strongly linked to current industry practices. While this is a desirable pursuit, there are considerable challenges in it being implemented owing to increasingly changing work environments and the notion of ‘industry currency’. One way for VET teachers to remain up to date with contemporary industrial practices is for VET to pursue teacher placement in industry (TPI) opportunities. TPI is an agreement in terms of which the VET teacher is seconded to a firm for a period of time in order to perform predefined tasks. The resulting benefits include enhanced teaching practices and the development of deeper, long-term links with industry. However, TPI opportunities are not without their challenges. This article reports on an exploratory study of the views of VET education managers of business studies on the value of TPI. Because management support is integral to creating TPI opportunities, we explored the extent to which TPI is desired and supported by education managers. We found that policies supporting TPI initiatives, if they are in place, are not well formulated, and that a lack of resources and difficulties in finding industry partners exist. Despite these problems, education managers believe that these activities are of value to teaching programmes and of benefit to their department. We conclude that TPI should be an integral part of any VET professional development for teachers, but that, in order for TPI to be successful, appropriate resourcing and the development of strong industry networks are paramount.

Voltage–current technique to identify fault location within long transmission lines

Current industry practice to identify fault location in transmission lines is based on visual inspection, travelling waves, and line impedance measurement. Unfortunately, these techniques are only developed to detect the fault location upon its occurrence without the ability to predict abnormal events that usually precede major faults and issue a timely warning signal to avoid potential consequences for power line failures. Furthermore, the current fault locating techniques exhibit some drawbacks that limit their wide practical implementation. This includes cost, access to required data, and low accuracy when employed for specific power line topologies. This study is aimed at presenting and validating a new cost-effective technique based on the line voltage–current characteristics to predict and identify the location of various abnormal and fault events in real-time. By measuring the currents and voltages at both ends of the line, a unique line fingerprint can be identified. Any change in this fingerprint can be detected and analysed by a software installed in the control centre in real-time to identify the location, type, and level of the abnormal events or emerging faults. Robustness of the proposed technique is assessed through simulation analysis conducted on various case studies along with a practical case study.