Packaging Line Research Articles

Adding hydrogen atoms to molecular models via fragment superimposition

BackgroundMost experimentally determined structures of biomolecules lack annotated hydrogen positions due to their low electron density. However, thorough structure analysis and simulations require knowledge about the positions of hydrogen atoms. Existing methods for their prediction are either limited to a certain range of molecules or only work effectively on small compounds.ResultsWe present a novel algorithm that compiles fragments of molecules with known hydrogen atom positions into a library. Using this library the method is able to predict hydrogen positions for molecules with similar moieties. We show that the method is able to accurately assign hydrogen atoms to most organic compounds including biomacromolecules, if a sufficiently large library is used.ConclusionsWe bundled the algorithm into the open-source Python package and command line program Hydride. Since usually no additional parametrization is necessary for the problem at hand, the software works out-of-box for a wide range of molecular systems usually within a few seconds of computation time. Hence, we believe that Hydride could be a valuable tool for structural biologists and biophysicists alike.

Studying the effect of optical system in quality control system of the medical instruments production applying computer vision

Computer vision is a solution to increase speed and accuracy in defect detection. The application of computer vision can only be highly effective with an optimally designed optical system that provides the computer vision system with data-optimised input images by displaying clearly on the photo the fault or defect on the product. To analysing the importance of high-quality input images, this paper provides optical solutions to the problem of computer vision error checking on the vaccine vial packaging line and single-use scalpel. At the same time, the authors will evaluate the critical needs of using a customised optical system for quality inspection on an assembly line.

Robotics for control strategy optimization and simulation in automatic cigarette sorter

In the world of advancement and rapid growth, new retail marketization and distribution require a substantial degree of versatility and resilience in the manufacturing plant to accommodate demand transitions. A Digital Matching Structure (DMS) is built such that real-time data from the framework for processing the physical goods can be aggregated and then translated into the digital context. A collaborative design approach is implemented in the DMS to automate stacked cigarette labelling and sorting. The periodic optimal decisions can be achieved from the joint optimization model by obtaining online details from the specific unit for the management network and then feeding them to the quasi-physical simulation platform in the DMS for validation of results. A sorting robot built-in DMS can be configured to catch and sort cigarettes on a conveyor belt to ensure high performance and eliminate the possibility of manual sorting. Digital Matching Structure – Sorting Robot (DMS-SR) is the solution recommended for the proposed integration. This article explores how finely packaged cigarettes are handled on the conveyor belt and how the packaging line works to understand and filter the product. The proposed integration method is assessed using appropriate mathematical models for validating its consistency and verifying the accuracy of sorting. Eventually, the proposed autonomous system parameters have been enhanced by tests on a real machine to boost the sorting performance. It was found that better sorting could be obtained when the conveyor speed of around 0.36 m/s. When there is sufficient load, growing the momentum and shortening the declaration/accelerationtime will produce the optimum efficacy. The DMS-SR currently has a sorting output of about 1900 cigarettes per hour, highly precise.

A Novel Approach to Cashew Nut Detection in Packaging and Quality Inspection Lines

YOLO standing for You Only Look Once is one of the most famous algorithms in computer vision used for detecting objects in a real-time environment. The newest version of this algorithm, namely YOLO with the seventh version or YOLOv7, is proposed in the present study for cashew nut detection (good, broken and not peeled) in packaging and quality inspection lines. Furthermore, this algorithm using an efficient convolutional neural network (CNN) to be able to successfully detect and identify unsatisfactory cashew nuts, such as chipped or burnt cashews. In order to deal with the quality inspection process, a new dataset called CASHEW dataset has been built at first by collecting cashew images in environments with different brightness and camera angles to ensure the model's effectiveness. The quality inspection of cashew nuts is tested with a huge number of YOLOv7 models and their effectiveness will also be evaluated. The experimental results show that all models are able to obtain high accuracy. Among them, the YOLOv7-tiny model employs the least number of parameters, i.e. 6.2M but has many output parameters with higher accuracy than that of some other YOLO models. As a result, the proposed approach should clearly be one of the most feasible solutions for the cashew’s quality inspection.

Adhesives for the Paper Packaging Industry: An Overview

Today, packaging plays a crucial role in maintaining the quality of products during uses by providing safeguarding against physical, chemical and environmental challenges. While polymer-based packaging material has been very extensively used, there has been a recent move to paper-based packaging products because of their economic and environmentally-friendly nature. Currently, Paper and paper-based board materials have been used as packaging material for food products, and e-commerce business. Adhesives in packaging industries are critical to the structure of most paper and paper board packaging, whether applied during the process of conversion and on the packaging line. From a production point of view, adhesive choice can significantly affect process line efficiency and production performance. Adhesive types used in paper industries are water-based adhesives both synthetic and bio-polymer based (starch, cellulose, protein and itaconic acid), Solvent-based adhesives (polyurethane and acrylic-based) and 100% solids adhesives like heat sealing adhesive and hot melts. More recently, water-based heat-expandable adhesive having thermally insulative and cushion-like properties has been provided for use in protective packages and wrap. Here, we aim to present an overview of the research trend of adhesives in the paper packaging industry. The overview summarizes the different adhesives for paper packaging industries.

Optimisation of multi-channel to single channel control method for food packaging line based on PLC

Optimisation of multi-channel to single channel control method for food packaging line based on PLC

Optimisation of multi-channel to single channel control method for food packaging line based on PLC

Optimisation of multi-channel to single channel control method for food packaging line based on PLC

Improved lentiviral vector titers from a multi-gene knockout packaging line

Lentiviral vectors (LVs) are robust delivery vehicles for gene therapy as they can efficiently integrate transgenes into host cell genomes. However, LVs with lengthy or complex expression cassettes typically are produced at low titers and have reduced gene transfer capacity, creating barriers for clinical and commercial applications. Modifications of the packaging cell line and methods may be able to produce complex vectors at higher titer and infectivity and may improve production of many different LVs. In this study, we identified two host restriction factors in HEK293T packaging cells that impeded LV production, 2'-5'-oligoadenylate synthetase 1 (OAS1) and low-density lipoprotein receptor (LDLR). Knocking out these two genes separately led to ∼2-fold increases in viral titer. We created a monoclonal cell line, CRISPRed HEK293T to Disrupt Antiviral Response (CHEDAR), by successively knocking out OAS1, LDLR, and PKR, a previously identified factor impeding LV titers. Packaging in CHEDAR yielded ∼7-fold increases in physical particles, full-length vector RNA, and vector titers. In addition, overexpressing transcription elongation factors, SPT4 and SPT5, during packaging improved the production of full-length vector RNA, thereby increasing titers by ∼2-fold. Packaging in CHEDAR with over-expression of SPT4 and SPT5 led to ∼11-fold increases of titers. These approaches improved the production of a variety of LVs, especially vectors with low titers or with internal promoters in the reverse orientation, and may be beneficial for multiple gene therapy applications.

OSTIR: open source translation initiation rate prediction.

SummaryTranslation of messenger RNAs into proteins by the ribosome is a fundamental step in gene expression. In bacteria, it is possible to accurately predict the rate of translation initiation from the sequence surrounding a gene’s start codon using thermodynamic models of RNA folding and ribosome binding. These predictions have applications in a range of fields, from systems biology studies that aim to understand and model bacterial physiology to synthetic biology studies that seek to reprogram bacterial cells. For example, metabolic engineers can design ribosome binding site (RBS) sequences to tune the expression of different enzymes in a pathway and thereby optimize the production of a desired chemical compound by cells. OSTIR (Open Source Translation Initiation Rates) is a Python package and command line tool for predicting translation initiation rates in bacteria.

Bottle Line Detection using Digital Image Processing with Machine Learning

Image processing is often used in industrial applications. The automatic visual inspection of a product before it is packaged and dispatched to the client is one of the most common uses for image processing. Using these types of systems in production facilities helps the avoidance of situations where a faulty or sub-standard product is shipped to the customer. The quantity of the fluid in each bottle differs with the accuracy level of the machine and furthermore due to mistakes done by employee during the underlying arrangement. Inappropriate filling during a bottle leads the makers to dispose of whole bunches of an item resulting in huge capital loss. A Economical mechanized review structure for inline packaging which detects oddities has been examined. The system are ending up being to be assign with checking the degree of the fluid filled inside each bottle as the container goes through the assessment framework introduced round the current packaging line. It will help to keep up the product quality and quantity as well and furthermore maintains the accuracy of the filling. The bit of the space between the outside of the fluid inside the bottle and container will be used to observe the differences like underfilling and overfilling. The proposed work is accomplished using image processing techniques in Machine Learning using python platform. Here we use ANN algorithm. Process of detecting the liquid level in bottle as follow as a group of pictures were given, taken under close to consistent lighting conditions in the manufacturing plant. These arrangement of pictures contains both underfilled and overfilled bottles which the packaging organization expects that you should use to identify certain issues as a component of the filling, covering and naming tasks before the final packing stage. The distance for each dataset must be same. We need to provide threshold value to detect if the bottle is overfilled or underfilled.

A dynamic model for the optimization of rotatory feeding devices

Component feeding is an important process in assembly and packaging lines, affecting the throughput. It is therefore important to optimize the feeding process with the aim of reducing the takt time of the production line. In kitting lines, the feeding devices are typically used to create little groups of components, preparing the batches for final grouping into a kit.In the paper, a dynamic model is developed and validated, which describes the interaction of the components to be fed with the blades of a rotating feeding unit. Then, an optimization method is proposed based on the dynamic model using a weighted cost function, which allows to define the shape of the blade according to a set of design objectives.

Short-term scheduling of make-and-pack processes in the consumer goods industry using discrete-time and precedence-based MILP models

This work deals with the short-term scheduling of a two-stage continuous make-and-pack process with finite intermediate buffer and sequence-dependent changeovers from the consumer goods industry. In the present coupled layout of the plant under consideration, the two stages, product formulation and packaging, are directly coupled, i.e. the products of the formulation stage go directly to their dedicated unit in the packaging stage. As for different products either the formulation or the packaging stage can be the bottleneck due to a stage and product dependent processing rate. A gain in productivity can be obtained if the two stages are decoupled by a buffer so that the formulation lines and the packaging lines can both run at full capacity. To evaluate the benefit of introducing a buffer between the stages, a rigorous discrete-time mixed-integer linear programming (MILP) model was developed. As the results of the discrete-time model were unsatisfactory with respect to total plant downtime due to changeovers and idle times, a two-step solution strategy including a second immediate precedence-based MILP model was developed. As the problem is intractable for the planning horizons of interest, an order-decomposition strategy for both models that is enhanced by several heuristics, was incorporated in the solution strategy. It is demonstrated that the redesign of the production plant yields significant productivity improvements that can be realized using the proposed scheduling approach. The computational results on several real cases show that the increased modeling and development effort of the two-step solution strategy pays off in terms of solution quality and computation times.

Effect of sporulation conditions following solid-state cultivation on the resistance of Geobacillus stearothermophilus spores for use as bioindicators testing inactivation by H2O2

Geobacillus stearothermophilus spores play an essential role in the pharmaceutical and food industries as bioindicators (BI) to evaluate inactivation effects of hydrogen peroxide in processing and packaging lines' sterilization. Unstandardized, inconsistent BI production, as is the case for currently available commercial BI, can lead to variable resistances and incorrect test results. The solution to this problem could be the standardization of BI spore production. This study assessed the effects of sporulation temperature and pH on spore resistance in the production of G. stearothermophilus ATCC 7953 spores on solid-state agar. For this purpose, spores were produced under different sporulation conditions (51–63 °C, pH 6–8), and their resistance was determined by the D-value in 35% liquid hydrogen peroxide at 25 °C. Based on these data, a mathematical equation describing the resistance as a function of the sporulation conditions was derived. The analysis showed a quadratic effect of the sporulation temperature and a linear effect of the examined domain's pH on the resistance, without interactions between these factors. We observed the highest D25C,35%H2O2-value of 309 s at sporulation conditions of 57 °C and pH 6.0.

Measurement of changes in torsional stiffness of press‐formed paperboard packages induced by heat load utilizing a developed measuring device

AbstractThe press‐forming process and the effects of parameter variation on the forming process have attracted great interest lately. The dimensional accuracy of the formed trays and the rigidity and stability of the packages are crucial factors for functionality in packaging lines, especially in fast operating machinery. The torsional stiffness of trays must be at a sufficient level to ensure the functionality in subsequent processes and logistics. The objective of this study was to develop and build a device for measuring the torsional stiffness of whole tray packages, to verify its functionality and to investigate the effect of heat load transferred to paperboard material on the torsional stiffness of the formed trays. The operation of the novel torsional stiffness tester was confirmed, and the tester was found to be suitable for measuring the thermal response of the sample materials and the effect of the fibre direction. Thus, the analysed material does not need to have a homogeneous stiffness property since the differences are noticeable in the measurement results. In addition, the results indicate that tray blanks should be die cut in the machine direction of the paperboard. The torsional stiffness of the tray packages increases, and the outer dimensions decrease as a function of the heat input. The first feature is desirable for packaging functionality and the second feature can be compensated by competent packaging design. To conclude, the use of higher mould temperatures is recommendable if the integrity of the package material is not compromised.

Characterisation of the opening behavior of multilayer films with cohesive failure mechanism by in situ peel tests in the ESEM

In this work, peel tests inside the chamber of an ESEM ( in situ peel tests) are described with heat-sealed test specimens of packaging systems made of multilayer films that simulate different flexible packaging types, according to the packaging line used. The in situ peel tests provided evidence to describe the influence of three different main aspects of the packaging process in relation to the opening behavior of the sealing packages. The investigated aspects are the peel angle, the alignment angle between the orientation of the multilayer films and the seal, and the bulge formation as a consequence of inadequate sealing parameters. In situ peel tests enabled the differentiation between peel angle and local (micro) peel angle, which results from the overall stiffness of the multilayer structure film. Alignment angles of 90° and 45° were found to produce similar opening forces. Images showing the formation of various new local micro fissures on new planes during the in situ peel test explained how the opening force can be dramatically increased during the tearing of two sealed multilayer films.

Aquatronics in systems of liquid food products for packaging lines

Aquatronics in systems of liquid food products for packaging lines

BiSulfite Bolt: A bisulfite sequencing analysis platform

BackgroundBisulfite sequencing is commonly used to measure DNA methylation. Processing bisulfite sequencing data is often challenging owing to the computational demands of mapping a low-complexity, asymmetrical library and the lack of a unified processing toolset to produce an analysis-ready methylation matrix from read alignments. To address these shortcomings, we have developed BiSulfite Bolt (BSBolt), a fast and scalable bisulfite sequencing analysis platform. BSBolt performs a pre-alignment sequencing read assessment step to improve efficiency when handling asymmetrical bisulfite sequencing libraries.FindingsWe evaluated BSBolt against simulated and real bisulfite sequencing libraries. We found that BSBolt provides accurate and fast bisulfite sequencing alignments and methylation calls. We also compared BSBolt to several existing bisulfite alignment tools and found BSBolt outperforms Bismark, BSSeeker2, BISCUIT, and BWA-Meth based on alignment accuracy and methylation calling accuracy.ConclusionBSBolt offers streamlined processing of bisulfite sequencing data through an integrated toolset that offers support for simulation, alignment, methylation calling, and data aggregation. BSBolt is implemented as a Python package and command line utility for flexibility when building informatics pipelines. BSBolt is available at https://github.com/NuttyLogic/BSBolt under an MIT license.

Applying Lean Six Sigma Methodology to a Pharmaceutical Manufacturing Facility: A Case Study

This research examines a case study on the implementation of an effective approach to advanced Lean Six Sigma problem-solving within a pharmaceutical manufacturing site which manufactures acetaminophen (paracetamol containing pain relief) tablets. Though this study was completed in a single manufacturing company, the implementation of this study delivers important application and results that can be deployed in other such manufacturing companies. The manufacturing site faced backlogs in customer orders due to increased demand. Increased demand is due to brand popularity and recognition, product efficacy and a COVID 19 pandemic that intensified the demand for pain relief tablets in an already very busy site. With increased demand, to ensure timely deliveries, customer satisfaction and minimize delays, sources of site productivity losses and wastes needed to be analyzed and reduced or eliminated. Manufacturing Packaging line downtime was identified as one area of concern. The goal of the research was to introduce a problem-solving technique to reduce downtime within a manufacturing site without affecting the production required to fulfil customer demand while increasing product quality. The research utilized an integrated LSS methodology which identifies, stratifies and effectively eliminates non-value adding (waste) activities, by following a 7-step customized problem-solving methodology which resulted in complete elimination of the issue under investigation and savings of just under half a million dollars. The learnings are being deployed and leveraged worldwide across the pharmaceutical organizations parent site and sister sites. The presented results demonstrated that Lean Six Sigma methodology and tools are effective for accurate root causing of problems and enablers of implementation of continuous improvement.

An Experimental-Numerical Study on Curling Process for Metallic Caps Production

In the field of food industry, adoption of metallic caps for the storage of agri-food products is widespread. This type of caps is obtained through a sequence of forming processes executed on a tinplate. First, the plane metal sheet is deep drawn to obtain a cup whose edge is slightly shaped inward, then a curling process forms the edge into a hollow ring. This paper is focused on the curling, which allows to assess the final cap shape immediately before the application of the cups on the jars. Since the process is generally made on packaging lines with high production rates, the design of a proper curling machine needs to consider the effect of fatigue as well as maximum load values. Because of the different cap dimensions and shapes contemporary worked on the line, the loads definition is not easy. The scope of this work is the development of a model for the prediction of curling loads for different cap shapes and sizes. The analytical solutions, available in literature, together with numerical simulations of the process were compared to experimental compression tests made on two different caps type. Considerations on caps geometry and size influence on curling force represent a contribution to the fitness for service evaluation as well as a starting point for the design of new curling machines.

Impact of Milk and Milk Product of Tamil Nadu

Sampling and analysis occur along the milk processing train: from collection at farm level, to intake at the diary plant, the processing steps, and the end products. Milk has a short shelf life; however, products such as milk powders have allowed a global industry to be developed. Quality control tests are vital to support activities for hygiene and food standards to meet regulatory and customer demands. Multiples of chemical and microbiological contamination tests are undertaken. Hazard analysis testing strategies are necessary, but some tests may be redundant; it is therefore vital to identify product optimization quality control strategies. The time taken to undergo testing and turnaround time are rarely measured. The dairy industry is a traditional industry with a low margin commodity. Industry 4.0 vision for dairy manufacturing is to introduce the aspects of operational excellence and implementation of information and communications technologies. The dairy industries’ reply to Industry 4.0 is represented predominantly by proactive maintenance and optimization of production and logistical chains, such as robotic milking machines and processing and packaging line automation reinforced by sensors for rapid chemical and microbial analysis with improved and real-time data management. This chapter reviews the processing trains with suggestions for improved optimization.