Anti-Counterfeit Product System Using Blockchain Technology

Fake Products is a serious issue, as in today’s world we can’t really distinguish between real and fake product. And some people make these fake products just to make some profit without thinking about its impact on user and also affects company’s name, profit and sales. Blockchain technology can be used to detect whether the product is real or fake and assure user about the authenticity of the product. Blockchain is a trending technology and lot of applications are using this technology. Blockchain technology is the technology where information is stored in the form of blocks in many databases which is connected with the chains and it doesn’t require any third-party users for permission. Benefits of blockchain is that it is immutable and secure. It is decentralized and distributed. We can use Quick Response [1] (QR) code or an encrypted unique code which is a very efficient technique to detect fake product. When the QR code is scanned or the unique code in entered, it will redirect us to the blockchain containing the information of the product and provides us the details of the manufacturer and information of owner to make decision easy for buyer if they are looking to buy the product. Keywords: Blockchain, Fake Product, Ownership, QR code, Anti-counterfeit

The cyber-consciousness of environmental assessment: how environmental assessments evaluate the impacts of smart, connected, and digital technology

Digitally-enabled technologies are increasingly cyber-physical systems (CPS). They are networked in nature and made up of geographically dispersed components that manage and control data received from humans, equipment, and the environment. Researchers evaluating such technologies are thus challenged to include CPS subsystems and dynamics that might not be obvious components of a product system. Although analysts might assume CPS have negligible or purely beneficial impact on environmental outcomes, such assumptions require justification. As the physical environmental impacts of digital processes (e.g., cryptocurrency mining) gain attention, the need for explicit attention to CPS in environmental assessment becomes more salient. This review investigates how the peer-reviewed environmental assessment literature treats environmental implications of CPS, with a focus on journal articles published in English between 2010-2020. We identify nine CPS subsystems and dynamics addressed in this literature: energy system, digital equipment, non-digital equipment, automation & management, network infrastructure, direct costs, social & health effects, feedbacks, and cybersecurity. Based on these categories, we develop a “cyber-consciousness score” reflecting the extent to which the 115 studies that met our evaluation criteria address CPS, then summarize analytical methods and modeling techniques drawn from reviewed literature to facilitate routine inclusion of CPS in environmental assessment. We find that, given challenges in establishing system boundaries, limited standardization of how to evaluate CPS dynamics, and failure to recognize the role of CPS in a product system under evaluation, the extant environmental assessment literature in peer-reviewed journals largely ignores CPS subsystems and dynamics when evaluating digital or digitally-enabled technologies.

Measuring raw-material criticality of product systems through an economic product importance indicator: a case study of battery-electric vehicles

Purpose The concept of criticality concerns the probability and the possible impacts of shortages in raw-material supply and is usually applied to regional economies or specific industries. With more and more products being highly dependent on potentially critical raw materials, efforts are being made to also incorporate criticality into the framework of life cycle sustainability assessment (LCSA). However, there is still some need for methodological development of indicators to measure raw-material criticality in LCSA. Methods We therefore introduce ‘economic product importance’ (EPI) as a novel parameter for the product-specific evaluation of the relevance and significance of a certain raw material for a particular product system. We thereby consider both the actual raw-material flows (life cycle inventories) and the life cycle cost. The EPI thus represents a measure for the material-specific product-system vulnerability (another component being the substitutability). Combining the product-system vulnerability of a specific product system towards a certain raw material with the supply disruption probability of that same raw material then yields the product-system specific overall criticality with regard to that raw material. In order to demonstrate our novel approach, we apply it to a case study on a battery-electric vehicle. Results Since our approach accounts for the actual amounts of raw materials used in a product and relates their total share of costs to the overall costs of the product, no under- or over-estimation of the mere presence of the raw materials with respect to their relevance for the product system occurs. Consequently, raw materials, e.g. rare earth elements, which are regularly rated highly critical, do not necessarily reach higher criticality ranks within our approach, if they are either needed in very small amounts only or if their share in total costs of the respective product system is very low. Accordingly, in our case study on a battery-electric vehicle product system, most rare earth elements are ranked less critical than bulk materials such as copper or aluminium. Conclusion Our EPI approach constitutes a step forward towards a methodology for the raw-material criticality assessment within the LCSA framework, mainly because it allows a product-specific evaluation of product-system vulnerability. Furthermore, it is compatible with common methods for the supply disruption probability calculation — such as GeoPolRisk, ESP or ESSENZ — as well as with available substitutability evaluations. The practicability and usefulness of our approach has been shown by applying it to a battery-electric vehicle.

Environmental Impacts Associated with Intensive Production in Pig Farms in Mexico through Life Cycle Assessment

In this research, environmental impacts associated with the intensive production of pigs on a farm in Mexico were determined through the application of life cycle assessment methodology. The research was focused on the following stages of the product system: (i) pig rearing and growth phases; (ii) production operations in the pig-house; (iii) the supply of feed. The life cycle inventory database was mainly made up of data collected in field visits to local farms. The functional unit was defined as one finished swine weighing 124 kg. The results for the selected impact categories of carbon, water, and energy footprints were 538.62 kg CO2eq, 21.34 m3, and 1773.79 MJ, respectively. The greatest impact was generated in the final stages of pig fattening, mainly due to the large quantity of feed supplied. The impacts caused by operation of the pig farm were less significant, their contribution in all cases was less than a third of the total quantified values. The energy conversion of pig slurry improves the environmental performance of the product system by reducing the carbon footprint.

Industrial applications of digital twins

A digital twin (DT) is classically defined as the virtual replica of a real-world product, system, being, communities, even cities that are continuously updated with data from its physical counterpart, as well as its environment. It bridges the virtual cyberspace with the physical entities and, as such, is considered to be the pillar of Industry 4.0 and the innovation backbone of the future. A DT is created and used throughout the whole life cycle of the entity it replicates, from cradle to grave, so to speak. This article focuses on the present state of the art of DTs, concentrating on the use of DTs in industry in the context of smart manufacturing, especially from the point of view of plantwide optimization. The main capabilities of DTs (mirroring, shadowing and threading) are discussed in this context. The article concludes with a perspective on the future. This article is part of the theme issue ‘Towards symbiotic autonomous systems’.

RELIABILITY ANALYSIS IN CEMENT MILLS OF BERBER CEMENT FACTORY

Reliability is the probability that a product, system, or service will perform its intended function adequately for a specified period, or will operate in a defined environment without failure. In this research, the reliability of Berber cement mill studied. The data collected from the information section of Berber cement factory related to the milling section. It includes the daily production reports, the breakdown and the operating time. The operating time between two failures (TTF) was calculated from the daily report of the mill and then a match was made for the data with the probability distributions to find out what is the probability distribution corresponding to the distribution of these data. The best distribution is the Weibull distribution. the Minitab software was applied and then the distribution parameters for the data (measurement parameters c and the shape parameter d) were obtained and then the reliability of each part of the mill were calculated for each hour and the reliability of the system was calculated as a whole. The study found that the reliability of the system is 75% at the first hour of operation. It decreased during continuous operation to 58% due to the poor reliability of the heating system, which has a reliability of 72% and the reliability of the conveying and feeding belts of the clinker, which have a reliability of 75%.