Industrial End-users Research Articles

Effect of Canning Variables on Minerals Content of Bruchid Resistant, Maz-Type Common Bean Lines

Dried beans are rich in proteins and good in important micronutrients like potassium, magnesium, folate, iron and zinc. Canning is a conventional food preserving method in which beans and other products are sterilized by heat after placed in hermetically sealed containers. Screening of bean lines for micronutrient retention during canning is an important input for food industry, beans researcher and other end users. The objectives of this study was to evaluate minerals retention of canned maz-lines common beans. A total of 3 Maz-lines of common beans were evaluated under 9 different canning treatments. Accordingly, mineral contents of maz-type canned common beans were evaluated using atomic absorption spectrophotometer. The result showed maz-type common bean lines and canning variables significantly affects minerals content. The highest calcium (68.79mg/100g) and zinc (2.68mg/100g) were exhibited in Maz-200 common bean lines. Canning variables caused an increment of sodium and calcium contents. However, potassium and zinc contents of canned beans decreased as result of varied canning variables. Good retention of potassium was demonstrated in samples soaked at ambient temperature for 30minutes before blanched at 88°C for 30 minutes. Similarly, good retention of zinc was recorded for sample soaked at room temperature for 40 minutes followed blanched at 75°C for 40 minutes.

A multidisciplinary perspective on the present and future of particle imaging

The imaging of particulate media – encompassing both the imaging of the particles themselves, as well as the study of their dynamics and bulk properties and behaviours – is crucial to improving our understanding of a diverse range of phenomena and processes spanning numerous scientific disciplines and industrial sectors. Despite interdisciplinary interest in the field and the availability, and continuous development, of a wide range of different imaging techniques, there exist nonetheless a number of limitations of these techniques, and open challenges – both technical and non-technical – facing the field as a whole. In this perspective, we discuss in detail five such challenges, identified by a team of interdisciplinary experts spanning both academia and industry: how can we work toward the imaging of systems which are more ‘real-world-relevant’, both in terms of composition and scale? How can we extract detailed, quantitative information regarding stresses from such systems? How can we image processes which are both rapid and transient, when most current technologies can manage (at best) only one of these states? How can we ensure closer and more fruitful collaboration between the academics developing particle imaging technologies and the potential industrial end-users who stand to benefit from them? How can we improve the visibility of the field and the educational opportunities available to the potential next generation of particle technologists? As one may expect for such a broad range of questions, the answers to the above are diverse and numerous. However, there are certain key themes running through them. Above all, our work highlights a need for improved collaboration, be that in terms of experts in multiple different imaging technologies working together to perform multi-modal studies so as to address the technical limitations highlighted above, researchers and industry professionals finding new ways to engage, or academics co-creating open-source educational tools to support the next generation of particle imaging experts.

Development of pre‐startup safety review implementation tool for safe operation in process plant

AbstractA pre‐startup safety review (PSSR) is a formal review of a chemical manufacturing process to verify that critical areas of the affected process have been assessed and addressed before using the process. It can be a new process or after modification to an existing process or operating conditions. There is concern about full implementation compliance, including designing the PSSR program, preparing the process to perform PSSR, following PSSR action items, and approving the PSSR report. This study aims to develop a PSSR Implementation Tool (PSSR‐IT) via the Microsoft Excel platform. At the end of the self‐assessment process, the end users were provided with the value of the percentage of compliance with PSSR requirements and a thorough review process prior to the start‐up activities. A safety experts’ content validation index (CVI) was performed to ensure the tool's content was valid and sufficient for the PSSR process, followed by a case study. Feedback from process safety engineers and PSSR leaders as end users has been collected through the System Usability Scale (SUS). A total of 227 questions have been listed under 10 disciplines, including general info, operation, engineering, operational, process safety, health safety and environment (HSE), action log, final walk down, and approval that cover all essential aspects of review process prior to the start‐up activities with CVI value of 0.98, k = 0.67. SUS findings demonstrated that all industrial experts and end users believe the tool is suitable and reliable, with a score >85%. Utilizing the PSSR tool will help the industries promote and improve the process safety program at the workplace.

Effects of alternative pricing structures on electricity consumption and payments in the commercial and industrial sector

We investigate the distributional and welfare impacts when commercial and industrial (C&I) electricity end users face a dynamic pricing structure as opposed to a constant volumetric price with demand charge on individual users’ peak usage. While demand charge does not necessarily reduce the system-wide peak, it often constitutes a large share of C&I users’ payments. Hourly electricity consumption data for C&I users on O‘ahu, Hawai‘i, reveal that the fixed cost recovery associated with removing demand charge has both significant distributional impacts and considerable efficiency gains. Moreover, the rate reform can be regressive or progressive depending on how the fixed charge is allocated across users.

Interdisciplinary evaluation of a robot physically collaborating with workers.

Collaborative Robots-CoBots-are emerging as a promising technological aid for workers. To date, most CoBots merely share their workspace or collaborate without contact, with their human partners. We claim that robots would be much more beneficial if they physically collaborated with the worker, on high payload tasks. To move high payloads, while remaining safe, the robot should use two or more lightweight arms. In this work, we address the following question: to what extent can robots help workers in physical human-robot collaboration tasks? To find an answer, we have gathered an interdisciplinary group, spanning from an industrial end user to cognitive ergonomists, and including biomechanicians and roboticists. We drew inspiration from an industrial process realized repetitively by workers of the SME HANKAMP (Netherlands). Eleven participants replicated the process, without and with the help of a robot. During the task, we monitored the participants' biomechanical activity. After the task, the participants completed a survey with usability and acceptability measures; seven workers of the SME completed the same survey. The results of our research are the following. First, by applying-for the first time in collaborative robotics-Potvin's method, we show that the robot substantially reduces the participants' muscular effort. Second: we design and present an unprecedented method for measuring the robot reliability and reproducibility in collaborative scenarios. Third: by correlating the worker's effort with the power measured by the robot, we show that the two agents act in energetic synergy. Fourth: the participant's increasing level of experience with robots shifts his/her focus from the robot's overall functionality towards finer expectations. Last but not least: workers and participants are willing to work with the robot and think it is useful.

Canola variety, nitrogen, phosphorus, and sulfur fertilization affect yield, quality, and fatty acid profile

Canola yield and quality are important for food, feed, and industrial end-uses. There may be trade-offs between the agronomic and quality aspects of canola production depending on varietal traits and management. The objective of this work was to assess the effects of nitrogen (N), phosphorus (P), and sulfur (S) fertilization on agronomic and quality properties of canola varieties with distinct oleic acid contents. Nitrogen fertilization rates were 0, 25, 50, or 100 kg·ha−1, P rates were 0 or 30 kg·ha−1, and S rates were 0 or 20 kg·ha−1. Canola was grown in 2003, 2004, and 2005 at Brandon, a private farm close to Brandon, and at Lacombe, Canada. Canola yields averaged 2.36 t·ha−1 for conventional, 2.53 t·ha−1 for low, and 2.2 t·ha−1 for the high oleic acid varieties at maximum fertilization of N, P, and S. The high oleic acid variety averaged 75% oleic acid content, whereas the low variety averaged 65%, and the conventional variety 62%. Total saturated fatty acids were greatest with the conventional oleic acid variety, and tended to increase with N, decrease with S, and were not influenced by P. The high oleic acid variety yielded slightly less than the other two varieties but tended to have lower glucosinolate and saturated fatty acid contents. This work could have implications for human nutrition or other end-uses. Current canola varieties and fertility management should be studied to produce canola with quality tailored for the end use.

The use of a multi-sensor core scanner workflow as the backbone of a digital core repository

Abstract A core repository is a physical record of a country's or commercial organization's subsurface wealth. Some of the largest core repositories hold thousands of kilometres of core material and it is a challenge to turn this physical archive into an accessible digital resource for all. Non-destructive multi-sensor core logger, hyperspectral and X-ray imaging techniques offer a unique chance to rescue valuable data trapped within core samples, improving the way that a core repository delivers data to academic or industrial end users. Here we present a case study of an archived petroleum core acquired in 1985 at the Osprey Field, UK Continental Shelf. Data from the UK National Data Repository are augmented by a multi-sensor core logger, hyperspectral and X-ray dataset that is uploaded into a cloud-based digital repository. The data were analysed using a multi-variant analysis to reclassify the original lithological interpretations, uncovering a greater proportion of clay and cemented horizons than was previously interpreted. A workflow is established to optimize the use of legacy cores and exploit the abundance of data trapped within the core repository using continuous multi-sensor core scanning and imaging data, which are stored within the virtual environment for visualization and access to all.

Differentiation of Centella asiatica (L.) Urb. from Hydrocotyle umbellata L. using the trnH-psbA region, species-specific bands and anisocytic stomata as markers for quality control of raw materials and their products

Centella asiatica (L.) Urb. has been confused with Hydrocotyle umbellata L. in Thailand. The plants grow in the same habitat and look alike, making H. umbellata a potential adulterant species for C. asiatica. This study aimed to (i) establish reference markers of authentic C. asiatica and H. umbellata using DNA barcoding, thin-layer chromatography (TLC) and microscopic methods and (ii) determine whether H. umbellata adulterants are present in C. asiatica products in Thailand. Ribulose-bisphosphate carboxylase (rbcL), maturase K (matK), internal transcribed spacer (ITS) and chloroplast intergenic spacer (trnH-psbA) were identified as core DNA barcode regions that can be used to differentiate C. asiatica and H. umbellata. The trnH-psbA region showed the highest nucleotide variation between C. asiatica and H. umbellata and had distinct amplicon sizes of approximately 506 and 398 bp, respectively. TLC analysis revealed three distinct bands at Rf 0.20, 0.30 and 0.32 that could be used to differentiate C. asiatica and H. umbellata. Anisocytic stomata were present only in C. asiatica and were purposed as a microscopic marker. The trnH-psbA amplicon, TLC species-specific markers and anisocytic stomata were utilized to examine six Bua Bok products traded in Thailand. Agarose gel electrophoresis showed PCR amplicons at approximately 500 bp, TLC showed species-specific bands at Rf 0.20, 0.30 and 0.32, and anisocytic stomata were found in all products, confirming that all tested products were C. asiatica. These markers will benefit the herbal industry and other end users by allowing the detection of the adulterant species H. umbellata in C. asiatica raw materials and products.

15 Monoclonal Antibodies for 1-Hydroxypyrene Glucuronide (1-OHPyrG), Lateral Flow (LF) Tests and the Development of On-Site Polycyclic Aromatic Hydrocarbon (PAH) Biomonitoring

Abstract Objective Anti 1-OHPyrG sheep Mabs have been raised, characterised and employed in a sensitive and specific ELISA. The development of a LF test will enable the manufacture of a simple, rapid and cost-effective point of use test. On-site screening will allow employers to immediately confirm safe working practice and significantly increase the efficacy of biomonitoring. Methods A quantitative LF test has been developed which employs an anti-1-OHPyrG sMab to capture the PAH metabolite. The captured metabolite is visualised through a second Mab raised against the sMab-1-OHPyrG immune complex. This sandwich assay provides a positive correlation between the assay signal and biomarker concentration. The LF test can determine biomarker concentrations in non-occupationally exposed individuals and performance has been determined in a comparative study. Results A specific LF immunoassay, with a measuring range of 20-500pg/ml of 1-OHPyrG, can detect increasing levels of PAH metabolite in urine due to lifestyle factors (e.g. smoking and consumption of chargrilled food) in samples from non-occupationally exposed individuals. The LF determined concentrations compared well to literature values. Urines determined by LF and ELISA were in excellent agreement (R2=97, N=8). Conclusions Antibodies enable the development of quantitative LF tests, providing "real-time" analysis to occupational health professionals. On-site testing allows the immediate confirmation of safe working practice and provides immediate reassurance to those involved in potentially hazardous activities. An ‘app’ to support LF testing is now under development and a survey of potential industry end-users has highlighted the desired features.

A green cogeneration microgrid composed of water-source heat pumps, a gravity energy storage, and a bio-fueled gas turbine: Design and techno-economic optimization

Rapid population and economic growth, democratization, decarbonization, deregulation, decentralization, and digitization (5D) of energy sector, transformation in lifestyle, as well as subsidized supply of petroleum products contribute to peak electricity utilization. In summer, limited power generation of thermal units have caused an urgent need to storages and renewable energy sources (RES). To mitigate pollutants emitted from generation facilities, nearly zero-energy buildings are created using RES and energy storage technologies. Hence, this paper presents a green combined cooling and power (CCP) generation system for industrial applications. A bio-fueled gas turbine cycle is selected to produce power for supplying both electrical demand and energy requirement of cooling loads. Some water-source heat pumps (WSHPs) are economically dispatched to procure cooling loads. A gravity energy storage (GES) is optimally scheduled to charge surplus electricity by pumping water and lifting a piston within a container and discharge it during peak periods by falling the piston and returning the high-pressure water into a hydro-turbine. A mixed-integer nonlinear programming problem is modeled to find the optimum operating point of the proposed plant minimizing the total energy cost. Simulations are conducted on a real industrial end-user with four WSHPs under two cases without and with cooperation of GES.

An exploration of context and learning in endurance sports coaching.

This study explored contextual factors which influence coach learning of an international cohort of endurance sports coaches. Following ethical approval, 839 coaches, 612 coached athletes and 8,352 non-coached athletes participated in the research. A critical realist research philosophy was adopted, in which self-completion surveys were developed in consultation with coaches and industry end-users. The context was dominated by remote coaching practices and digital technology which shaped how coaches learn and thus, what it meant to be a coach. Unmediated learning sources were biophysically biased and largely delivered through marketised platforms designed to sell products. The study findings have broader implications within sport and education, in which it is suggested that remote coaching and learning platforms may sometimes create a sense of psycho-emotional detachment in which capacity for learning can be limited.

Metabolomic analysis of methyl jasmonate treatment on phytocannabinoid production in Cannabis sativa.

Cannabis sativa is a multi-use and chemically complex plant which is utilized for food, fiber, and medicine. Plants produce a class of psychoactive and medicinally important specialized metabolites referred to as phytocannabinoids (PCs). The phytohormone methyl jasmonate (MeJA) is a naturally occurring methyl ester of jasmonic acid and a product of oxylipin biosynthesis which initiates and regulates the biosynthesis of a broad range of specialized metabolites across a number of diverse plant lineages. While the effects of exogenous MeJA application on PC production has been reported, treatments have been constrained to a narrow molar range and to the targeted analysis of a small number of compounds. Using high-resolution mass spectrometry with data-dependent acquisition, we examined the global metabolomic effects of MeJA in C. sativa to explore oxylipin-mediated regulation of PC biosynthesis and accumulation. A dose-response relationship was observed, with an almost two-fold increase in PC content found in inflorescences of female clones treated with 15 mM MeJA compared to the control group. Comparison of the inflorescence metabolome across MeJA treatments coupled with targeted transcript analysis was used to elucidate key regulatory components contributing to PC production and metabolism more broadly. Revealing these biological signatures improves our understanding of the role of the oxylipin pathway in C. sativa and provides putative molecular targets for the metabolic engineering and optimization of chemical phenotype for medicinal and industrial end-uses.

Ultra-Low Losses SiC-Based Active Damper for Industrial Power Systems: Mitigating Harmonic Distortion and Maximizing Harmonic Power Recovery

Wideband harmonics and undamped resonances have become problems of major concern for industrial end-users in the last time. Although passive dampers are the simplest solution to combat the mentioned problems, passive dampers convert the harmonic active power ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$P_{H}$</tex-math></inline-formula> ) they absorb to heat, leading to energy waste. Conversely, active dampers not only reduce harmonic distortion and suppress resonances but can also perform harmonic power recovery. In effect, harmonic power recovery implies transforming the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$P_{H}$</tex-math></inline-formula> absorbed into fundamental active power that is injected back into the power system. This paper introduces a mathematical model that describes the mechanisms and necessary conditions of harmonic power recovery within an active damper. The model shows that a substantial amount of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$P_{H}$</tex-math></inline-formula> can be recovered only if the active damper's power losses are significantly smaller than the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$P_{H}$</tex-math></inline-formula> absorbed. Consequently, this paper presents the implementation of an ultra-low losses 82 kVA active damper based on SiC MOSFETs which recovers around 80% of the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$P_{H}$</tex-math></inline-formula> absorbed. Moreover, a comparative experimental evaluation was carried out between the proposed active damper and an IGBT-based active damper. The comparison shows that the amount of harmonic power recovered can be increased by a factor of four using the SiC-based active damper.

Bi-level optimization of a near-zero-emission integrated energy system considering electricity-hydrogen-gas nexus: A two-stage framework aiming at economic and environmental benefits

Decarbonization is increasingly highlighted to realize emission peak and neutrality targets, while relevant low-carbon measures remain price high, especially for industrial end-users. This paper thus focuses on a specific design for park-level integrated energy systems with near-zero emissions. Solar photovoltaic and distributed wind power are applied as the main power supply together with the help of the local grid. The decarbonization sector is composed of power-to-gas (P2G) and carbon capture units where electrolyzers are separated from P2G and constitute the hydrogen subsystem together with hydrogen tanks and fuel cells. The system is also considered under the dynamic market environment where electricity, hydrogen, and emission exchanges are included. Then, the system behaviors are determined by an optimal operation model considering an uncertain power supply. Based on the stochastic operation, system configuration optimization considering economic and environmental objectives is constructed as a multi-objective integral model that is solved by an enhanced firefly algorithm in the first stage. Next, the optimal result is concluded according to subjective judgment and objective distribution in the second one. A case study in Gansu province, China is carried out to validate the system, and results indicate that 1) optimal result investing 5.285 million $ could avoid 7.4542 kilotons of emissions annually with a 20.1 % loss of self-power supply rate on average, 2) up to 51.72 kg of hydrogen fuels or 47.90 kg of gas could be generated besides daily load satisfaction, 3) carbon exchange incentive above 4.2 $/t could promote additional emission reduction.

Experimental Investigation into Liquid and Solid Separation by an Industrial Mesh-Vane-Type Separator on Natural Gas at 4–5 MPa, Different Liquid Loadings and Gas Flows

AbstractInline vertical separators are commonly employed in natural gas transmission facilities (e.g., receipt stations) to filter liquid contaminants such as compressor oil, glycol, and free water from the gas stream. Manufacturers of these separators have claimed liquid removal efficiencies of 98–99% for droplet sizes ≥ 8 μm. However, these contaminants have been found invariably in piping systems downstream of these separators, suggesting inadequate separator performance. Currently, there is a lack of ability to verify manufacturer claims due to difficulties in quantifying liquid contaminants and droplet characteristics. The potential consequences of having such contaminants include lower gas quality, impaired gas metering accuracy, corrosion and damage to equipment/instrumentation, and adverse impacts on industrial and residential end users. This paper presents performance testing of a mesh-vane-type vertical separator conducted on high pressure, pipeline quality, natural gas in the range of 4–5 MPa and flow velocity in the range of 1.3–13 m/s in the DN150 separator inlet (hence turndown ratio of 10:1). Four different spray nozzles were used to inject and atomize industrial compressor oil with a liquid-to-gas mass loading ratio of 0.06–1.8%. Test results revealed that the average bulk efficiency separation performance for this separator is approximately 90.34%. This was found to be independent of the liquid-to-gas mass loading ratio. The effective Souders–Brown K-factor was found to be 0.15 m/s. This is below literature published data in the range of 0.27–0.3 m/s for horizontal flow, vane-pack-type separators. Liquid separation tests were also conducted following the injection of solid glass beads. Liquid separation efficiency decreased by approximately 9%, following the injection of 7 kg of industrial glass beads over a period of approximately 4 h. This was attributed to accumulation of solids in the vane pack.

A Novel Generalized Predictive Control Strategy With Improved Time Domain Performance

Abstract Due to the ability of handling the coupling property of multivariable control system, generalized predictive control (GPC) has been widely employed in process industry. However, the existing GPC method normally utilizes the frequency domain indices in the design procedure, which is not intuitive to the industrial end users. Therefore, a new GPC method with improved time domain performance is proposed for multiple-input-multiple-output system. First, the slope and rate of change of the slope of the system outputs are considered as two new weighting terms in the cost function of GPC such that the dynamic characteristics of the system can be better considered in the optimal control problem of the controller. Second, given the modified cost function, the resultant GPC algorithm is developed to improve the time domain performance of the system. Third, the convergence and stability of the closed-loop system under the proposed method are theoretically proved. Finally, the experimental results based on the variable air volume (VAV) air conditioning system show that the time domain performance indices, including overshoot and settling time, of the proposed method, have been improved by 68.75% and 66.67%, compared with the traditional GPC, showing the advantages of the new GPC method.

Knowledge-Based Trust: Linking Transparency to Trust in Google Search Algorithm

Given the controversies over the efficacy of algorithm transparency within political conflicts among agencies, this study examined whether there are discrepancies between a user’s perceived and received transparency and trust in Google’s algorithm-based search engine. Drawing on the concepts of perceived transparency, actual transparency, and trust, this study conducted a moderation mediation analysis along with the bootstrapping method to investigate 1) whether there are gaps between perceived transparency in Google Search and the actual understanding of the system, i.e., received transparency; and 2) how gaps in transparency affect the extent of user trust in search engines. The main findings suggested that received and perceived transparency are important for improving user trust in the search system. In particular, our results supported a knowledge-based trust model that achieves greater trust through a process linking transparency perception with actual understanding of the system. This result challenges the industrial sector’s aggressive logic of algorithm secrecy by implying the benefits of greater openness, thereby shedding light on a reciprocal relationship between industrial actors and end users.

On the application of the anisotropic enhanced thermal conductivity approach to thermal modelling of laser-based powder bed fusion processes

Computational simulation of the Powder Bed Fusion (PBF) process is a useful tool for predicting and analysing melt pool geometry during the deposition process. Advanced models that use Computational Fluid Dynamics (CFD) can accurately simulate the complex melt pool dynamics of the process but are typically computationally onerous to implement. CFD models require thermophysical data over a large temperature range that may be difficult to acquire for the material systems of interest. Heat conduction models, which are useful to industrial end users are easier to implement, but their accuracy can be compromised. The main difference between heat conduction and CFD modelling is the absence of convection (especially Marangoni convection). However, several sources in literature have highlighted a simple approach to mimicking the effects of Marangoni convection on the melt pool by artificially increasing the thermal conductivity of the liquid. However, due to its simplicity and lack of agreement within literature, the modified heat conduction approach is neither sufficiently robust nor universally consistent. Comparison to experimental data is lacking. In the present work, the heat conduction model is modified using an orthotropic description of anisotropic thermal conductivity in the liquid phase by applying directional correction factors. The correction factors are calibrated by comparing the predicted geometry against experimentally-obtained melt pool dimensions for single-layer, multiple tracks in Ti-6Al-4V processed by laser-PBF. After appropriate correction factors were selected, the modified heat conduction model gave results in good agreement with experiments. To test the general applicability of the approach, data from literature were analysed and simulated using the model. After correction factors were adjusted accordingly, the simulated results were validated over the range of power levels and scan speeds. • Transient thermal conduction model of the laser-based powder bed fusion process. • Melt pool geometry simulated using efficient modelling approach. • Track profile simulated with consolidated deposition geometry on the substrate. • Good agreement with bespoke experimental data and independent data from literature.

Industrial End-Users’ Preferred Characteristics for Wood Biomass Feedstocks

The use of sustainably sourced biomass is an important tool for mitigating the effects of climate change; but biomass is far from being a homogeneous resource. The aim of this study was to examine the decision-making process of industrial end-users considering biomass procurement. An online, two-part survey generated responses from 27 experienced professionals, representing a portfolio of facilities varying in size, technology, and biomass types, across Australia, Canada, Finland, and Sweden. A PAPRIKA conjoint analysis approach was used to analyze the data so that the attributes that influenced procurement decisions could be weighted and ranked. The results provided an insight into end-users’ views on factors including facility location, size, and biomass storage, handling, and procurement for different wood-based industrial services. The most important decision-making attribute appeared to be the type of biomass assortment, at individual, national, and aggregated levels. Of seven sub-categories of biomass assortments, sawdust (35%) was the most preferred type followed by stem wood chips (20%) and energy wood (15%). We concluded that, from the end-user’s perspective, a pre-defined biomass assortment is the most important factor when deciding on feedstock procurement at a bioenergy facility. These results help us better understand end-users’ perceptions of biomass properties in relation to their conversion processes and supply preferences and can inform product development and the securement of new niches in alternative business environments by existing and future biohubs.

Resource Selection from Edge-Cloud for IIoT and Blockchain-Based Applications in Industry 4.0/5.0

Industrial Internet of Things (IIoT) is attempting to integrate the real world into the digital world through smart devices, information technology, and Internet. IIoT is connecting enormous devices in industry 4.0/5.0 which may be heterogeneous in nature. With the evolution of IoT, diverse technologies have been employed to deliver the quality of services to the end users in a seamless manner. Cloud computing has considerably boosted the growth of IIoT by serving the computational and data storage needs of IIoT- and blockchain-based applications in industry 4.0/5.0. However, cloud is providing services to IIoT users, but still, there is a need to improve the latency rate of delivery of services, the transmission rate of end-to-end delivery, and overall throughput of the network channels in industry 4.0 and blockchain-based distributed systems. The cloud servers those are located at remote locations are not capable to offer the quality of services to users who require real-time responses, minimum network latency, and optimum throughput. The advancements in Edge computing are making Edge-Cloud more suitable for end users in blockchain-based transactions and industry 4.0 to serve the requirements of IIoT-based applications. This paper aims at providing the resources of Edge-Cloud to the end users by proposing a soft-computing technique for selecting the most suitable resources from the pool of available resources at Edge-Cloud. This paper is proposing a multicriteria statistical approach for resource selection to exploit the benefits of Edge-Cloud and to suffice the needs of IIoT and blockchain-based applications in industry 4.0. The results obtained from the proposed research assist in enhancing the service providing rate, minimizing the delay in transmission, and optimizing the throughput of Edge-Cloud servers.