Processing Factory Research Articles

A framework for development of digital twin industrial robot production lines based on a mechatronics approach

During the past years, intelligent manufacturing has attracted enormous attention from both academia and industry. Smart factories/workshops/production lines are important carriers for realizing intelligent manufacturing. However, there are difficulties in smart factories in processing multi-source heterogeneous data, in integrating virtual and physical worlds, and in achieving continuous and iterative optimization with real-time feedback. Digital twin, which is able to deeply integrate physical and virtual worlds, provides an important technology for easing the difficulties mentioned above. The construction of a digital twin system can solve the problem of data fusion, analysis, processing, and applications in smart factory. Digital production lines are the foothold of a smart factory. Building a digital twin production line can facilitate rapid practice of digital twins and promote the development of intelligent manufacturing. To this end, this paper proposes a development framework for a digital twin production line with closed-loop control based on a mechatronics approach. The detailed development process is given based on the framework. The framework proposed may provide some inspiration and insights for design and development of digital twin production lines.

Vetiver Floating Wetlands for Dyeing Effluent

As a result of industrialization, the degree of global water contamination has drastically grown in recent decades. Both rich and developing nations are seeing this worldwide trend, although the later are experiencing it more pronouncedly. Due to its extraordinary and distinctive morphological and physiological characteristics, the Vetiver Floating Wetlands (VFWs), which is based on Vetiver grass (Chrysopogon zizanioides), has been successfully used as a phytoremediation tool to remediate both polluted water like municipal wastewater such as sewage effluent, landfill leachate, urban runoff, drainage channels, industrial wastewater such as food processing factories, and contaminated land (mine overburden and tailings, solid waste dumps). This study focuses on the use of hydroponics and floating wetlands to clean contaminated dyeing effluent. This study aims to find the efficiency of Vetiver Floating wetlands over various physio-chemical parameters in Dyeing effluent. The study was laid down in Tamil Nadu Agricultural University, Coimbatore in 2022 during the month of April- May. The effluent was diluted to different concentrations namely 25%, 50%, 75% and 100%. Various parameters were analyzed in these treatments in Dyeing effluent. The samples were collected at 15 days interval analyzed for one month. In Dyeing effluent, 50% concentration of the effluent showed better results over Vetiver Floating Wetlands and the removal efficiency was greater at this particular concentration.

Sistem Tataniaga Tandan Buah Segar (TBS) Kelapa Sawit (Studi Kasus di Desa Tegar, Kecamatan Mandau, Kabupaten Bengkalis, Provinsi Riau)

Fresh Oil Palm Bunches Trading System (Case Study of Tegar Village, Mandau District, Bengkalis Regency, Riau Province). Oil palm is one of the leading commodities in Mandau District with a total production of 812,927.8 tons. Unfortunately, this large production has not been facilitated by an efficient trading system, especially when viewed from the benefits received by farmers in Tegar Village. This study aims to analyze the trading system, trading channels and trading costs, as well as the share margin received by each of the trading channels of fresh oil palm bunches in Tegar Village, Mandau District, Bengkalis Regency. 30 farmer respondents were selected using purposive sampling technique. Using qualitative and quantitative analysis, this study shows that the trading system of fresh oil palm bunches in Tegar Village is a one channel trading pattern, in which farmers sell to intermediary traders, who then transport the fresh oil palm bunches to palm oil processing factories. The trading system analysis result shows that the margin value in this channel is 14.23%, with farmer's share of 85.77%, and a profit ratio of 43.60%. Operationally this channel is an efficient channel.

Analysis of the Implementation of Enterprise Resources Plan (ERP) on Company Performance (Case Study of PT Sapta Sentosa Jaya Abadi)

PT Sapta Sentosa Jaya Abadi is a plantation company located in four different provinces. The company operates the oil palm business (cultivation and processing factory). The company was founded in 2002. Previously the company relied on manual operation in every of their administration, realizing the importance of building an information system based on Enterprise Resources Plan (ERP), the company collaborated with third parties s developed ERP which they called Go Palms. Indeed, Go Palm makes work easier and ultimately improves the company's performance, but performance data from 2016 to 2020, actually shows a downward trend. Lack of socialisation, makes employees as users find it difficult both in adapting and using information systems in their work to find out how the role of information systems drives performance, the authors researched the role of ERP on company performance through Quality of Information Systems. The research method used is quantitative with the Regression Analysis Approach as a data processing method. The research was conducted on all 10ERP users. The results show that: 1) there is a simultaneous influence of Go Palm's Information System Quality on the Company's Performance; 2) There is a partial effect of Product Operation on Company Performance; 3) there is no partial effect of Product Revision on Company Performance, and; 4) There is a partial effect of Product Transition on Company Performance at PT. Sapta Sentosa Jaya Abadi. The suggestion in this study is that management needs to carry out socialization and training related to the use of the ERP system, so the employees know why they need to do work using an ERP information system and also the benefits they can get. Keywords: Enterprise Resources Plan (ERP), Performance Appraisal Management, Quality of Information System.

ANALISIS RANTAI PASOK PADA KOMODITAS KOPRA DI DESA LOWIAN KECAMATAN MAESAAN KABUPATEN MINAHASA SELATAN

The study aims to identify supply chains based on product flow, information flow, financial flow and analyze the level of marketing efficiency in the copra commodity supply chain. This research was carried out for three months, from August to October 2021, which took place in Lowian Village, Maesaan District, South Minahasa Regency. This study uses primary data and secondary data. The population in this study were all coconut farmers and copra collectors. Sampling using a simple random sampling method (simple random sampling) obtained 50 farmers from a population of 248 farmers and 3 traders collectors. The results showed that the supply chain in Lowian Village was based on product flow from upstream to downstream starting from copra farmers, collectors, and copra processing factories. The flow of information flows from two directions, namely the first direction the factory provides information to traders about the quality and price of copra needed then traders provide price information to farmers, the second direction is farmers provide information to traders about the quality of copra sold then traders will inform the factory about the volume marketing of copra to be sold. As for the financial flows from downstream to upstream, starting from factories that buy copra from collecting traders via bank transfer, then collecting traders buy copra from farmers with a cash payment system. The level of marketing efficiency in the copra supply chain seen from the total marketing margin, marketing costs and profits has been efficient.

Geographical Distribution of Three Forest Invasive Beetle Species in Romania.

Simple SummaryBiological invasions in the forests of Europe are becoming more frequent, and bark- and wood-boring insects are increasingly important invasive forest pests. Global trade intensification facilitates the introduction and spread of these species across new areas, while climate change and humans contribute to their establishment and spread. If such species enter new territories, the application of appropriate management measures requires—among other things—a better knowledge of their distribution. Using traps with different attractants, we attempted to establish the current distribution in Romania of three of the beetle species that are predicted to be important forest pests: Ips duplicatus, Xylosandrus germanus and Neoclytus acuminatus.Ips duplicatus (Sahlberg, 1836), Xylosandrus germanus (Blandford, 1894) and Neoclytus acuminatus (Fabricius, 1775) are invasive species reported in Romania, but their current distribution is poorly known. The research aim was to provide new information on this issue. A survey was conducted over the period 2015–2017 in 82 locations, using flight-interception traps and bottle traps, baited with different attractants. Data obtained in our other unpublished studies were also taken into account. A total of 35,136 I. duplicatus beetles were collected in 30 survey locations. The highest captures were in the log yards of some factories processing logs of Norway spruce (Picea abies (L.) H. Karst.). Considering all known records so far, most of these are in the eastern part of Romania, where an outbreak took place during the years 2005–2014, mainly in spruce stands growing outside their natural range. During the survey, 4259 specimens of X. germanus were collected in 35 locations, but in our other studies the species was found in 13 additional places. It was collected at altitudes of 18–1200 m, and the largest catches were from beech stands, growing at 450–950 m. N. acuminatus was found in only six locations, in the western and southern parts of the country, at low altitudes, in tree stands composed of Fraxinus excelsior L., Quercus spp. and other broadleaf species, as well as in broadleaf log yards. The results suggest that I. duplicatus is established in most parts of the Norway spruce’s range, X. germanus is still spreading in the country, with some areas having quite high populations, while N. acuminatus is present only in the warmest regions of the country.

Effects of COVID-19 on environmental conditions and poultry production

Although hens are not vulnerable to SARS-CoV-2, there have been a number of coronavirus illness outbreaks reported in connection with poultry processing plants in various nations. The COVID-19 pandemic and the created strain triggered the second, third, and most current waves of epidemics, which had unforeseen effects such being obliged to reduce demand for certain sectors, transit systems, jobs, and enterprises owing to public confinement. Additionally, because of the close closeness on the line, the cold, and the humidity, the circumstances in chicken processing factories increase the dangers. Due to poor pay and lack of access to paid sick days or proper healthcare, the majority of employees have little money saved up in case they choose to quit their stable jobs. Additionally, employees at meat and poultry slaughterhouses may get an infection via touching filthy workstations, dining room tables, or equipment, as well as from respiratory droplets in the air. Due to consumer behaviour changes brought on by the lockout, egg costs have climbed significantly. Over the next months, the COVID epidemic may have a significant influence on the world poultry trade as well. The impact of COVID-19 on chicken production, environmental sustainability, and earth systems will be the main emphasis of this study from many process angles.

Design of Green Tea Drying System Using Smoke and Temperature Sensors Based on Microcontroller

The green tea drying process still uses wood as its fuel because it can reduce production costs. However, the smoke produced by the bottom firewood enters the drying chamber, thus affecting the quality of the green tea produced. Therefore, it is necessary to have a drying system that can detect and control the smoke entering the drying chamber and control the temperature during the drying process. The tea drying system is designed using a smoke sensor and a temperature sensor based on a microcontroller. This system is also equipped with an RH sensor that can monitor the RH value during the drying process. From the device performance test results, it was found that the system designed can control the smoke and temperature in the drying chamber to be applied to the green tea drying process in tea factories.

Assessment of Occupational Noise Generation and Associated Noise-Induced Hearing Loss among Employees of a Black Tea Processing Factory in Darjeeling District, India.

Exposure to high levels of noise is a problem among tea factory workers worldwide, but it is poorly studied in India. This study aimed to assess noise generation in various parts of a black tea factory and find out prevalence of occupational noise-induced hearing loss (ONIHL) and its determinants among employees. An observational cross-sectional study was performed in a black tea processing factory of Darjeeling District. Noise levels and exposure data at different parts of the factory were measured using a sound level meter. Participant characteristics were obtained using a questionnaire and noise-induced hearing loss data obtained by audiometry. A sound map was generated based on noise exposure data and a multivariable logistic regression performed to assess determinants of ONIHL. Sound pressure levels ranged from 58.7 to 90.3 dBA, with the highest levels in the crushing-tearing-curling (CTC) room. Noise exposure of workers was the highest during curling process and the lowest during packaging in the packing room. The prevalence of ONIHL was found to be 28.3%, most of which were of moderate degree, and the highest prevalence was among CTC room workers. Multivariable analysis showed significant association only between daily noise exposure and the presence of ONIHL (AOR 1.68, P value = 0.018). None of the study participants used any hearing protection equipment during work. Generation of high levels of noise is a pertinent problem in the black tea factory, which, coupled with non-use of personal protective equipment, led to a high risk and prevalence of ONIHL.

Impacts of COVID-19 on at-sea data collection and regulatory activities and fisheries catches off Namibia

This study was undertaken to: (i) comprehend the observers’ perceptions of COVID-19 and identify its impacts on the observation of harvesting, handling, and processing of marine resources, and biological data collection during commercial fishing, (ii) assess the risk of contracting COVID-19 onboard the fishing vessels, (iii) compare fishery catches for the pre-COVID-19 (2018 and 2019) and COVID-19 (2020 and 2021) years, and (iv) suggest possible ways to mitigate the impacts of COVID-19 on the activities of at sea-observations and data collection. Thus, 45 Namibian fisheries observers were interviewed by telephone to capture their perceptions of COVID-19 on the sea-observations and biological data collection. Messrooms were the riskiest places (45.7%) onboard the fishing vessel where observers perceived likely to contract COVID-19. For at-sea observations, 57.1% of the respondents felt that COVID-19 has negatively impacted observations as fisheries observers were risk-averse, especially in the processing factories. Half of the participants purported a negative impact on the collection of biological data, as on some vessels fisheries observers were not permitted to sample the fish supposedly for fear of cross-contamination. Analysis of fisheries observation data and fisheries catch data showed a significant difference in the total number of fishing trips made between 2018 and 2021 (X2=145.34, df = 3, p < 0.05), with a notable reduction in 2020 fishing trips. Similarly, the number of observed fishing trips between 2018 and 2021 differed significantly (X2=136.80, df = 3, p < 0.05). Fishing catches were lowest in 2020, possibly reflecting severe impacts of COVID-19 in that year. Understanding the impact of COVID-19 on at-sea observation and data collection can inform decision makers to improve management of marine resources during COVID-19 pandemic. Findings from this study can also serve as a lesson for nations that use observer data for stock assessment.

Spatial modeling for the potential location of a rubber processing factory in East Ogan Komering Ulu (OKU) Regency, South Sumatra Province

This study uses spatial modeling to determine the potential location of a rubber processing factory in East Ogan Komering Ulu (OKU), South Sumatra, Indonesia. This descriptive study used the map overlay method. Besides, this study also used six parameters, namely number of population, rubber plantation area, land slope, land suitability, river flow availability, and road network availability. Those six parameters were overlaid and scored to generate a map of the potential location for the rubber processing factory in East OKU, South Sumatra, Indonesia. Our analysis results suggest that the most potential location was 27.412 ha (9 percent), while the area with medium and low potential was 267.952 ha (86 percent) and 15.155 ha (5 percent), respectively. Generally, the pattern of the most potential area followed the road network pattern and river network in East OKU because both road and river facilitate the provision of water resources, as well as distribution of raw materials and produced products. These results can be used as a reference for the government of East OKU Regency in constructing the factory. Besides, this study can also be used as a Geography learning material in the course of map and mapping, as well as Geography Information System.

A Hybrid Optimization Algorithm for Water Volume Adjustment Problem in District Heating Systems

Nowadays, the winter is getting harsher and harsher in Northern China. Thus, the centralized heating systems (CHSs) are playing even more irreplaceable, essential and critical roles in ensuring general public’s livelihood than never ever before. CHSs are normally composed of one or several combined heat and power (CHP) plants (units) and an extensive vein like district heating networks (DHNs) connecting with chemical plants, paper mills, food processing factories, hospitals, hotels, universities, prisons and residential complexes. A CHP plant in Northern China usually consumes coal to heat the cold water into steam to drive high-pressure turbines and low pressure turbines to generate electricity. Then the low-temperature steam is used to heat up the cold water in a main pipe into hot water travelling through the DHNs to provide heat to each end nodes. The returned water will be heated again for reuse and the surplus steam will be released into air through cooling towers. In 2020, China promised to the world that carbon dioxide will peak in 2030 and net-zero emission will happen in 2060. On the one hand, CHP plants need to guarantee enough hot water flowing within each household’s heating radiator. On the other hand, they should cut down on the consumption on non-renewable resources. Lowering water temperature, adjusting water volume and reducing water pressure will all contribute to energy-saving purpose. Lowering water temperature and reducing water pressure may cause too much heat losses during long-distance transmission in frigid winter. Therefore, a reasonable water volume adjustment becomes an advisable action comparatively. Here, we transfer the hot water supply volume optimization problem (HWSVOP) into a heat exchange station (HES) valve angle adjustment problem (SHWESVAAP). Then, a multi-objective mathematical model is established considering balancing the satisfactory degree of each household in residential quarters and the hot water volume (HWV) in the main pipe. And a hybrid polar bear optimization algorithm integrated with chemical reaction optimization (HA-PBO-CRO) is designed to optimize the valve angle (VA) in each HES. The comparative results between HA-PBO-CRO and non-dominant sorting genetic algorithm (NSGAII) demonstrate HA-PBO-CRO is superior to NSGAII with better Pareto frontiers on one hand and provide a critical reference supporting the management in a CHP plant to make a right decision on what to do to cut energy consumption while satisfying customers’ needs.

The comprehensive improvement of surface integrity in whirlwind milling a large screw

The surface integrity of a large screw in whirlwind milling was vital for the fatigue life. Firstly, the comprehensive evaluation of surface integrity (CESI) was modeled by the Analytic Hierarchy Process (AHP). The weights of selected important factors, such as surface roughness (Ra), surface residue stress (SRS), and full width at half maximum (FWHM), were calculated. Then aimed at minimizing Ra, SRS −200 MPa and maximizing FWHM, the single-factor improvements were achieved under different parameter combination, respectively. Lastly based on single-factor improvements, the CESI was markedly improved by 64% compared to factory processing. Thus, the proposed approach and methodology can be notably adequate for evaluating and improving the surface integrity comprehensively.

An Inexpensive CRISPR-Based Point-of-Care Test for the Identification of Meat Species and Meat Products.

The growing demand for and supply of meat and meat products has led to a proportional increase in cases of meat adulteration. Adulterated meat poses serious economic and health consequences globally. Current laboratory methods for meat species identification require specialized equipment with limited field applications. This study developed an inexpensive, point-of-care Loop-Mediated Isothermal Amplification (LAMP)-CRISPR/Cas12a colorimetric assay to detect meat species using a Texas Red-labelled single-strand (ssDNA) reporter. As low as 1.0 pg/µL of the porcine NADH4, the chicken NADH dehydrogenase subunit 2 (ND2) and the duck D-loop genes was detectable under white, blue and ultraviolet light. The test turnaround time from DNA extraction to visualization was approximately 40 min. The assay accurately detected pure and mixed-meat products in the laboratory (n = 15) and during a pilot point-of-care test (n = 8) in a food processing factory. The results are 100% reproducible using lateral flow detection strips and the real-time PCR detection instrument. This technology is fully deployable and usable in any standard room. Thus, our study demonstrates that this method is a straightforward, specific, sensitive, point-of-care test (POCT) adaptable to various outlets such as customs, quarantine units and meat import/export departments.

Improvement of industrial processes in Colombia. Case study: Cocoa pressing process in a chocolate factory

This work explored an industrial-scale cocoa liquor pressing process used to obtain two standard fat-reduced cocoa powders with 12% and 16% wt. fat, respectively. A novel methodology was developed to sample and characterize fat content in cocoa cakes as released from the press before the powdering. Cocoa liquors with ~ 53% wt. fat, and with solids containing maximum ~1% wt. of particle below mesh 200 were pressed at 90 °C, and up to 550 bar following a specific time-pressure profile. Fat content in samples was measured with a pulsed nuclear magnetic resonance spectrometer. Experiments enabled to evaluate the variability of fat content of products from different batches, in different cakes from a batch, and within the cakes, verifying large average deviations (~ 5% wt.). By using a Kernel canonical correlation analysis with a Kriging interpolation approach, it was possible to map the fat content profile within the cakes, enabling to identify suitable sampling areas in the cakes for consistent and more accurate measurements of fat content in the product. Finally, the developed methodology was used to characterize different pressing batches at the industrial facility, and to correlate the required processing time for a specific fat content in the liquor.

Identification of Emission Source Using a Micro Sampler Carried by a Drone

A micro needle trap sampler (NTS) was carried by a mini quadrotor drone (Mavic Pro, DJI) to collect volatile organic compounds (VOCs) from industries. The NTS was fabricated using a 7 cm long, 22-gauge stainless steel needle by packing powdered divinylbenzene (DVB) adsorbents (60–80 mesh diameters). The telescoping sampling shaft was installed on the drone to extend the NTS beyond the downward air turbulence that was caused by the rotation of its propellers. The total mass of the sampling device, including an NTS, a telescoping shaft, a mini-air pump, and an ABS (acrylonitrile butadiene styrene) rack, was not more than 200 g. The emitted VOCs, those from a steel processing plant, including aromatic hydrocarbons (toluene of 15 ppb, ethylbenzene of 9 ppb and p-xylene 12 ppb), and those from a semiconductor processing factory, including trace amounts of methanol (1.96–2.00 ppm), acetone (0.05–0.10 ppm), and toluene (1.04–2.00 ppm), were extracted by the NTS on the drone and identified using a gas chromatography-mass spectroscopy (GC-MS) system in the laboratory. According to the results of VOC detection during the sampling flight of a drone, the stationary pollution sources were successfully identified.

An analysis on the domestic fish marketing of south Andaman

The domestic fish marketing of fish landing centre of south Andaman was analysed. The study has undertaken between January and February, 2022 in two fish landing centres (FLCs) of South Andaman namely Wandoor and Junglighat. Around 9 fishery cooperative societies marketing personnel were interviewed by adopting semistructured interview method and daily visit to landing centre has been done to analyse the structure and pattern of fish marketing system in both the FLCs (Table 1). This exercise has undertaken to meet different marketing personnel nearby portblair region and ideate about the interventions which could be planned for improving the infrastructure facilities and innovations in the marketing system (Table 2). It is observed that the marketing costs incurred by each of the intermediaries has been increasing day by day in Junglighat fish market and less involvement in Wandoor landing centre. Lack of proper communication facility with the island while fishing, inadequacy of maintenance yards for crafts and gears, lack of launching and landing facilities for crafts and gears in many areas, lack of processing factories and inadequate training for fishermen by the fisheries department are the infrastructural constraints pointed out by the fishermen at landing centre.

Machine learning classification of surface fracture in ultra-precision diamond turning using CSI intensity map images

With increasing focus on automation of machining processes in a smart factory, attention has turned to implementation of machine learning (ML) not only for tasks such as process parameter optimization, tool wear monitoring, and surface roughness prediction, but also for near-real-time determination of part quality using image data for inline inspection. As a first step, this work compares the performance of ML approaches using post-process image data, as opposed to numerical machining process data, for the discrete prediction of surface fracture in single-point diamond turned germanium for IR optics. Typical classifiers such as Random Forest and Support Vector Machine are employed for processing numerical machining parameters, while feedforward neural networks (FNNs), convolutional neural networks (CNNs), and deep CNNs (DCNNs) are utilized for processing intensity map images of the turned surfaces. The feasibility of using FNNs, CNNs, and DCNNs for identifying fracture in intensity maps is initially explored on raw images, and then by employing edge segmentation and edge detection techniques such as the Sobel, Prewitt, and Laplacian operators, as well as denoising methods as the Adaptive Gaussian Threshold filter. Finally, hybrid CNN and hybrid FNN models that combine numerical process data and image data are explored.Keywords

Editorial

In this first Editorial of 2022, I am happy to welcome Dr. Martin Braun of Intel to our Editorial Board. Dr. Braun has a long record of distinguished accomplishments in the semiconductor industry with Texas Instruments and Intel in a variety of roles. He brings to TSM his expertise in advanced process control, data analytics and factory and supply chain management. We look forward to working with him these coming years.

Online Anomaly Detection of Industrial IoT Based on Hybrid Machine Learning Architecture.

Industrial IoT (IIoT) in Industry 4.0 integrates everything at the level of information technology with the level of technology of operation and aims to improve Business to Business (B2B) services (from production to public services). It includes Machine to Machine (M2M) interaction either for process control (e.g., factory processes, fleet tracking) or as part of self-organizing cyber-physical distributed control systems without human intervention. A critical factor in completing the abovementioned actions is the development of intelligent software systems in the context of automatic control of the business environment, with the ability to analyze in real-time the existing equipment through the available interfaces (hardware-in-the-loop). In this spirit, this paper presents an advanced intelligent approach to real-time monitoring of the operation of industrial equipment. A hybrid novel methodology that combines memory neural networks is used, and Bayesian methods that examine a variety of characteristic quantities of vibration signals that are exported in the field of time, with the aim of real-time detection of abnormalities in active IIoT equipment are also used.