Quality Traceability Research Articles

Intelligent Micron Optical Character Recognition of DFB Chip Using Deep Convolutional Neural Network

The microcharacter recognition on the distributed feedback (DFB) laser chip is critically essential but a challenging task for the quality control in the incoming chip inspection and optical device manufacturing lines. Hence, this article proposes, designs, and implements a micro-optical character recognition system based on the microscopic imaging system and deep convolutional neural network to facilitate the microcharacter recognition of DFB chips. The proposed micron optical character recognition (MOCR) contains four components, namely, a microscopic imaging system-based visual-based measurement (VBM), character detection, orientation correction, and character recognition. In particular, data augmentation methods considering limited datasets and some chip character features are studied so as to accommodate complex industrial environments and tiny DFB chips. Experiments from the DFB image dataset of a real optical device manufacturing line showed that it reached the accuracy of 98.8%, which took a high speed of over 12.8 fps coping with DFB chip images, and saved 72% of the labor in the inspection position compared to traditional methods. To the best of our knowledge, there are no existing reports focused on MOCR on DFB chips. So, the first realization and successful application of MOCR played a key role in the intelligent manufacturing and quality traceability of DFB chips and devices in the field of optical communications, which is also of great significance for further accelerating the development of the industrial Internet.

Consortium blockchains based traceability system for chicken product supply chain

In recent years, people pay increasing attention to food safety. Chicken, as the second largest meat consumer goods in China, requires high level quality traceability. However, due to the small monomer and large quantity of live poultry, it is difficult to duplicate the whole chain tracing mode of pig industry. In this paper we use HACCP (Hazard Analysis and Critical Control Points) to analyze the key control points in the chicken supply chain, and design the traceability code for each chicken product. The traceability system applies the consortium blockchains technology to realize the secure and trusted up-chaining of traceability data, which ensures the quality and safety of chicken in the market.

A residual dense comprehensively regulated convolutional neural network to identify spectral information for egg quality traceability.

In the egg market, due to the different nutritional values of eggs laid by hens under different feeding conditions, it is common for low-quality eggs to be counterfeited as high-quality eggs. This paper proposes a residual dense comprehensively regulated convolutional neural network (RDCR-Net) to identify the quality of eggs laid by hens under different feeding conditions. Firstly, a hyperspectral system is used to obtain the spectral information of eggs. Secondly, due to the complex structure of the spectral information, a comprehensively regulated convolution (CRConv) is proposed to extract features hidden in the spectral information through feature transformation in multiple spaces. Thirdly, due to the limited availability of spectral information training samples, deep networks may suffer from feature degradation. The residual dense comprehensively regulated block (RDCR-Block) is proposed to tightly connect multiple CRConv layers with residual dense connections. Finally, the RDCR-Block is taken as the central unit, and the RDCR-Net is designed to identify egg spectral information. In the comparison of multi-model results, the RDCR-Net obtains the best classification performance with 96.29% accuracy, 97.53% precision, 97.14% recall, and 96.19% kappa coefficient. In summary, the RDCR-Net effectively extracts the deep features of spectral information, achieves high accuracy in identifying eggs laid by hens under different feeding conditions, and provides a new method for egg quality traceability.

Concurrent Engineering and based Applications for 3D Big Data

European companies’ competitiveness depends on obtaining innovative products. In the last years, clients demand started to be higher and more complex. Because of that, managing products development processes have become a necessity. Product development processes need to be proficient and flexible: less complex and more competence-focused. 3DSpace brings more solutions in this matter. EXALEAD transforms large volumes of heterogeneous, multi-source data into real-time information intelligence to help users improve business processes and gain competitive advantage. EXALEAD enables organizations to gather and enrich Big Data to deliver that information in the process of integrated product development and allows customers to fully manage product programs, from 3D design to traceability of changes, cost, quality and issue analytics. Concurrent or Simultaneous Engineering is one of the fundamental approaches that meet the challenges mentioned above. EXALEAD uses CloudView to process big data flows. Concurrent Engineering represents a standardized approach to integrated product improvement which accentuates and gives priority to the customer expectations level. In this matter, 3DSpace’s ENOVIA is used together with graphic software for manufacturing. It is about teamwork and confidence in which the decision-making process is consensual, even from the beginning of the product life cycle.

Enabling Supply Chain Visibility and Compliance Through Voluntary Information Sharing With Customs: A Case Study of the Global Quality Traceability System in China Customs

The promotion of digital customs and data analytics have led customs administrations to seek to improve their analytics capabilities and exploit data from the trade community. Despite the increased data analysis capabilities of Customs, the data available to them are still limited to the current mandated declaration. If businesses are willing to share additional commercial information with Customs, it will enable them to make a more accurate risk assessment and ensure compliance. As a new form of Customs and business partnership, voluntary information sharing can be a supplementary data source to the mandated declaration and enable Customs to exploit additional commercial information. This study analysed an exploratory case study on the Global Quality Traceability System (GQTS) initiated by China Customs to investigate how voluntary information sharing can be achieved, and to explore the benefits for the participants. This study demonstrated that voluntary information sharing with Customs implemented through a data pipeline enhanced supply chain visibility and ensured compliance. The private companies who shared information contributed to the supply chain visibility and in return benefited from it.

Worth of Artificial Intelligence in the Epoch of Modern Livestock Farming: A Review

Artificial intelligence (AI) is a human intelligence in machine encountered daily and impacts our lives. It is expected that the use of such technology in the livestock industry will automate the livestock processes and easy to manage. Biometric identification plays a key role in artificial intelligence which shows the individual identity, helps in the process of insurance and claim leakages, continue monitoring of farm animal is essential can be done with new technologies. Infra red temperature measurement camera is the newly added technology with sensor system in (AI). It is a temperature measuring device in the form of electromagnetic waves and the infrared radiation intensity. AI system consists of agent, sensor, actuators and effectors which are connected to cloud. It helps in the detection of estrus, animal diseases, body condition score and various physiological parameters using video surveillance data collection method. Artificial neural network is a branch of artificial intelligence (AI) which is based on a collection of connected units or nodes called artificial neurons and stored in a central database system. Sustainable economic future of dairy farms and to achieve 100% compliance rate. Modern dairy farms uses robotic system to deliver vaccines, machine milking and measurement of feed as per individual performance of the animal. AI analyzes the animal origin food quality traceability method from farm to fork. AI helps in the complete mechanized animal husbandry right from the birth of animal to production and food product. The future of AI in animal sector is not predictable, but advantages and daily increasing demand of AI over other sector will ensure future in animal sector as well.

Modeling and analysis of a quality traceability framework for phosphate extraction process: evidence from Morocco

PurposeAccording to United Nations reports, the worldwide population is expected to reach around 9.6 billion by 2050. This forecasting emphasizes the role of phosphate-based fertilizers for developing sustainable agriculture and ensures the demand all over the planet. From this perspective, phosphate companies are racing to improve their industrial performance and guarantee the quality, reliability and integrity of information efficiently. The purpose of this paper is to propose a traceability system framework that ensures product quality tracing and real-time operations monitoring for open-pit mines.Design/methodology/approachThe authors develop a hybrid approach that integrates Business Process Model and Notation techniques with System Modeling Language to formalize several use cases and scenarios to model quality traceability processes related to open-pit mines. This framework also embeds an optimization module based on mathematical modeling approaches to optimize stockpiles’ movement and respect the distinction between different qualities.FindingsThis paper explains a successful implementation of a quality traceability tool for an African mining company. The research team was able to understand and scale down the problem faced by the managers. Further, the study is focused on improving quality tracing over time and automatizing the current compliance processes related to the mine extraction activities. The proposed tool is proved highly effective in reducing the time of tracing quality claims by 46% compared with the manual procedure. Second, the implementation of this tool reduced fuel costs by 34% and CO2 emissions by 10%.Originality/valueThe originality of the contributions lies in four aspects: (1) adapting quality traceability concept for the mining industry; (2) assessing the current trends of traceability systems considering the mining industry context; (3) hybridizing business processes re-engineering, quality system and optimization modeling; and (4) using a real case study of a phosphate company to evaluate the framework.

Organization of the wheat flour quality traceability

Currently, the problems of quality and safety of food products are the most important for the processing enterprises of the agro-industrial complex. Increasingly important are activities aimed at improving the quality of the life cycle processes of food products. One of the basic foods in the diet of most consumers is bread and bakery products, and the main raw material for their production is flour. Therefore, the topic under consideration of our paper is relevant.

A digital twin-driven approach towards traceability and dynamic control for processing quality

Processing quality is the basis for ensuring product quality, and reflects the development needs and application value of realizing intelligent manufacturing. Aiming at the low efficiency of quality problems traceability, poor timeliness and unpredictability of quality control in the machining process, digital twin technology can provide a new intelligent solution based on interaction and integration between physical workshop and virtual workshop. Therefore, a digital twin-driven approach towards traceability and dynamic control for processing quality is proposed in the paper. Firstly, a Bayesian network model for the analysis of factors affecting processing quality (BN_PQ) is introduced, which determines the relevance and influence weight of each factor to processing quality. Secondly, in order to integrate multi-source heterogeneous data to trace the processing quality, a multi-level scalable information model and association mechanism are established. Moreover, the construction method of the IoT system in manufacturing unit for dynamic control of processing quality are introduced, in which the collection method of real-time data is discussed. The contents of digital twin data for processing quality constraints (DTD_PQ) and the management method are elaborated. Then, the digital twin-driven dynamic control method of processing quality is proposed. The conceptual model of the digital twin database and the operating logic for dynamic control of processing quality are described in detail. Finally, the interactive operation and core technologies of DTD_PQ towards traceability and dynamic control of processing quality are analyzed. By choosing examples of machining the connecting rod of diesel engine and the prototype system that has been developed, the effectiveness of the proposed method is verified.

Analytical Comparison of Pregnancy-Associated Plasma Protein-A (PAPP-A) Immunoassays for Biochemical Determination of Gestational Age.

Accurate pregnancy dating is critical for maternal and child health and for counseling on safe and effective abortion methods. While last menstrual period and first trimester ultrasound are often used together to determine gestational age (GA), they have limited accuracy and availability, respectively. Prior studies have shown that pregnancy-associated plasma protein-A (PAPP-A) increases exponentially during pregnancy and has the potential to serve as a biochemical marker of GA. We aimed to analyze the relationship between sonographically determined GA and serum PAPP-A concentration measured by different immunoassays and to derive cutoff levels informative for the 70 days GA commonly recommended limit for medical abortion in outpatient settings. We compared technical characteristics of 4 commercially available PAPP-A immunoassays and tested 120 maternal serum samples (GA range: 34-231 days) along with contrived pool samples and traceable quality controls. These characteristics included area under the receiver operator characteristic (AUROC) plot, sensitivity and specificity based on cutoffs defined by the Youden Index, and likelihood ratios. All 4 immunoassays had sensitivities and specificities ≥80%, and AUROC values ranging from 0.948 to 0.968. Marked differences among absolute PAPP-A values were noted depending on immunoassay. PAPP-A cutoff values at 70 days GA for each individual immunoassay were established along with procedural recommendations that increase equivalence among immunoassays. Maternal serum PAPP-A levels correlated strongly with GA despite differences in immunoassay formats and absolute data output. Serum PAPP-A has biomarker potential for future development of a point-of-care test aimed at increasing access to medical abortion.

A blockchain-based system to enhance aircraft parts traceability and trackability for inventory management

Aircraft spare parts inventory management (ASPM) has played a critical role in tracing and tracking spare parts as any related maintenance or movement shall be recorded. Traceability and trackability of data ensure the compliance of airworthiness requirements. The International Air Transport Association (IATA) has strongly emphasised the significance of quality traceability data throughout the aircraft part’s life cycle, leading to enhanced inventory control accuracy, reduced maintenance error, and effective decision-making processes. However, with the rapid increase of spare parts types, the complexity of aircraft parts multi-stage supply chains leads to inefficient tracing and tracking operations with unsatisfactory traceability data quality and information security. This paper proposed a blockchain-based system that provided a managerial platform for accurate recording of spare parts traceability data with organisational consensus and validation using Hyperledger Fabric and Hyperledger Composer. A data model has been determined based on the existing ASPM, enabling information integrity during transaction operations. The channel mechanism has yielded a trustful data sharing platform between each contracting organisation for logistics and operational arrangements, which has enhanced information visibility and security. The blockchain-based system, executed under a decentralised ledger mechanism, shall improve the quality of traceability data and reliable information sharing within the spare parts supply chain. The enhanced blockchain-based inventory management system can establish the digital twin of aviation as part of Industry 4.0 in the future.

Role of non-pharmacological interventions for healthy ageing.

The range of non-pharmacological interventions (NPIs) available for people over 60 years of age is continuously expanding, both in terms of prevention and therapy. They have been empirically selected for centuries and more recently developed through epigenetic studies, clinical trials and technological innovations, and their development has increased and diversified around the world. Residual questions concern: 1) the scope of such treatments which appears to overlap with alternative medicines, 2) their evaluation, which some researchers say is impossible, and 3) their implementation in the elderly, which appears to be overly complicated. This article addresses these three questions and presents digital tools developed by the CEPS University Platform facilitating the evaluation of NPIs in the field of healthy aging. The transformation of the health system, which has become necessary to meet the needs of baby boomers, will widen the arsenal of health-related solutions. The combination of approaches to medicine and health has become personalised, comprehensive and integrative. NPIs will play a major role in the coming century. These practices differ from alternative medicines, general public health messages and socio-cultural approaches through continuous research, a quality approach and traceability of use. NPIs today constitute a complementary ecosystem for biomedical treatments which are increasingly becoming economically and legally consolidated.

BLOCKCHAIN TECHNOLOGY INTO STEEL INDUSTRY CURRENT STATE OF FOREIGN PAYMENT ACTIVITY

The purpose of the article is to analyze the current state of foreign trade in the industrial blockchain of the steel industry, the existing digital platform has gradually formed a large-scale heterogeneous distributed environment. The problems of further development of the metallurgical complex of Ukraine in the world electronic system of international cooperation are determined. Methodology. The survey is based on a blockchain technology is an interlinked systematic chain of blocks that contains transaction history and other user data. It works under the principle of decentralized distributed digital ledger. Results. Experimental tests prove that production companies, logistics, international payments and consumers can participate in the information certification of steel products via the modern information system. Consumers can understand the real product manufacturing process, effectively avoiding of the incomplete information and low transparency in the traditional information traceability process, and effectively trace the quality of steel products. The system provides an effective payments scheme for promoting the transformation and upgrading of the modern technology steel industry. Practical implications. In view of the low transparency of information traceability of current steel products and the defects of information islands, in this article the blockchain-based steel smart contract payment technology quality traceability system is developed and adopted the alliance chain mode and the new digital blockchain platform. The article describes the use of smart payment technology in a full-fledged financial transaction as a transfer funds in cryptocurrency to electronic bank accounts, as well as the transfer of commercial information, including contracts. To do this, the assets and terms of the contract are encoded and placed in the block chain, then the contract is distributed is saved on a set of network nodes and is executed after the condition is triggered. The fulfillment of the obligations of the parties is checked automatically. It is worth noting that the fact that smart contracts only react to transactions. If the asset or the currency is transferred to the program, it starts monitor compliance with the terms of the contract. How as soon as they are fulfilled, the seller receives money, and the buyer is a shipment goods. Value/originality. Blockchain technologies enable the use of business information systems that are highly resistant to technical failures and malicious attacks. Costs and time of carrying out business operations are significant.

Research on application of internet of things technology in quality traceability of fruit and vegetable agricultural products

The quality and safety of agricultural products are related to public health, social stability, and national development. The Internet of Things technology plays a vital role in the traceability of agricultural product quality. The Internet of Things coding and marking technology enables complete traceability of agricultural product supply chain process data. This article first proposes a low-cost, high-performance Internet of Things quality traceability identification code for fruits, vegetables, and agricultural products based on Internet of Things technology-Han Xin code, which has low production cost, large information capacity, strong anti-fouling and distortion ability, and reliability. High technical characteristics. Then, a miniaturization-oriented, IPv6-based Linux server and HBuilder development platform were used to construct a quality traceability system for fruit, vegetable and agricultural products in Hanxin Code. The results show that the Hanxin code coding technology designs a low-cost quality traceability implementation plan for fruit and vegetable agricultural products, and realizes the whole process monitoring of fruit and vegetable agricultural products from planting, picking, storage to sales, and has good practical value.

Physicochemical, antioxidant and FTIR-ATR spectroscopy evaluation of Kashmiri honeys as food quality traceability and Himalayan brand.

Three types of honeys viz. Robinia pseudoacacia (RSA), Plectranthus rugosus (PR) and multifloral honey (MF) from Kashmir Himalayas of India were characterized on the basis of physicochemical, antioxidant and FTIR-ATR spectroscopic features. The physicochemical parameters indicated that ash content, electrical conductivity, redness (a*) and yellowness (b*) were higher in MF honey, moisture content, Hydroxymethylfurfural (HMF) and lightness (L*) in PR honey and Water activity (aw) and proline content in RSA honey (P ≤ 0.05). Significantly higher values of total sugar, total reducing sugar and sucrose content was observed in MF honey (P ≤ 0.05). The total phenolic content (TPC), total flavonoids, ferric reducing antioxidant power and 1, 1-diphenyl-2-picrylhydrazy-IC50 (DPPH- IC50) free radical scavenging activity showed that MF honey had significantly higher antioxidant activity (P ≤ 0.05). ATR-FTIR analysis demonstrated that the absence of peaks at broad band around 1653.454-1637.656cm-1 in MF honey, 1185.989-1153.072cm-1 and 918.570-916.544cm-1 wavenumbers in PR honey thus clearly discriminating different types of honeys. The results revealed that physico-chemical, antioxidant and spectroscopic characteristics of honey types vary with geographic origin and their floral sources and MF honey have a high therapeutic potential.

Research on quality traceability of cigarette by combining PDCA quality cycle with information strategy based on fuzzy classification

For the weak part of the quality traceability ability of cigarette logistics and products, this paper proposes a quality traceability method which integrates PDCA quality cycle with information strategy. This method firstly establishes the quality cycle process of cigarette logistics through PDCA quality cycle process, and then constructs IS-PDCA process based on information strategy (IS) to analyze the quality traceability process of cigarette products. The key links are determined according to the traceability process of cigarette logistics, and the traceability resource scheduling function is determined through the product. Then, according to the determined scheduling function and RFID technology, the optimal allocation strategy is constructed to complete the feature extraction and classification identification of cigarette quality labels. For assessing the quality of cigarette evaluation, classification based on fuzzy is proposed and artificial neural network are utilized for calculating the grade of cigarette. Finally, a process of cigarette quality traceability combining PDCA quality cycle and information strategy is formed, and the quality traceability results are constructed by means of QR code technology, so as to realize the process system of cigarette quality traceability and improve the quality control ability of cigarettes. The simulation results show that the cigarette quality traceability method constructed in this paper can obtain the cigarette quality control with good adaptive performance, and the control process shows a strong ability, which improves the feasibility and effectiveness of the cigarette quality traceability.

An Integrated Supplier-Buyer Lots Sampling Plan With Quality Traceability Based on Process Loss Restricted Consideration

Supplier-buyer relationships have been the focus of considerable supply chain management and marketing research for decades. To validate the process capability of a supplier, practitioners usually operate the acceptance sampling plan (ASP). The most basic ASP is a single sampling plan (SSP) due to its straightforward lot-disposition mechanism. However, since the lot-disposition mechanism of SSP cannot accommodate the historical lot-quality levels information, it requires a large sample size for inspection to validate the submitted lot's process capability. To obtain these benefits from historical information, multiple-lot dependent state (MDS) sampling plans have been proposed. The MDS plans have manufacturing traceability of historical lot-quality levels information to sentence the submitted lot. However, the MDS plan's manufacturing traceability has a drawback that cost-efficiency decreases as more historical lot-quality levels information are considered, which contradicts its initial development goal. To overturn this contradictory situation, we proposed the adaptive MDS (AMDS) plans based on the process loss restricted consideration with combinatorial mathematical treatment that can correct the MDS plans manufacturing traceability of historical lot-quality levels information that help practitioners to adopt more historical information into lot-disposition freely without bearing the reduction of cost-efficiency. Meanwhile, their performances are superior to existing MDS plans in terms of cost-effectiveness and discriminatory power. Moreover, we further developed a web-based app for our proposed plans to improve the convenience of applying them in practice. By operating the web-based app, practitioners can quickly obtain the optimal plan criteria without bearing the burdens of table-checking or mathematical model solving. These improvements can genuinely help buyers distinguish reliable suppliers efficiently and build up a strong partnership with them. Finally, the applicability of the proposed plan is demonstrated in a real-world case study.

Retracted] Urban Fruit Quality Traceability Model Based on Smart Contract for Internet of Things

In Internet of things, compared with the traditional traceability system, the existing system has difficulties in operation, data are easily lost, data are uncoordinated, standards are not unified, and so on. In this paper, based on the characteristics of blockchain, the traceability model of urban fruits is established to reduce the risk of counterfeit and shoddy urban fruits. The collected data is integrated into the chain for diversified display, providing different permissions and platforms for multiple roles. Blockchain and supporting intelligent hardware are used to realize the real record and tracking of the whole process of fruit. Improve the transparency and efficiency of supply chain, and reduce the supply chain cost. The experimental results show that the proposed algorithm model can be applied to the fruit service field and effectively improve the service level of smart city.

Research and Practice of Agricultural Product Quality Traceability Social Intercourse Application

The social intercourse application of agricultural product quality traceability is facing historical opportunities such as the growth of member agriculture, consumption upgrading and grading, rapid development of social media and social services in the current internet era. This research divides the users of social intercourse application of agricultural product quality traceability into producers, consumers and distributors, and points out that the application should have the features of being open and easy to spread, free of charge and easy to access, interesting and attractive, real-time and interactive and for dissemination, it can be carried out through searching and subscribing the producers, recording and forwarding the content, as well as scanning agricultural product traceability QR code. Based on the above-mentioned methods and ideas, the “Nongdu Easy to Trace” Wechat program based on Wechat platform has been developed and has been widely promoted and used in many provinces in China.

Blockchain and Technologies Matching with the Case of Study of Vegetables Production

The proposed work describes a new approach based on supply chain traceability by blockchain (BC). The basic BC network has been designed and applied for vegetables process monitoring and tracing. The paper proposes some results of an industry research project by describing the whole scenario, the architectures implementing BC, the sequence diagram principle, and the prototype network embedding blocks and transactions. The discussion is also addressed on the possibility to combine different technique such as artificial intelligence, and image processing to improve pre-cut vegetable quality. The paper proposed preliminary results proves that the adopted technologies and the methodologies found in the literature are suitable for the sanitation process certification and for quality traceability. The mentioned approaches are useful to apply the suggested frameworks for other supply chains.