Knowledge-Based Virtual Modeling and Simulation of Manufacturing Processes for Industry 4.0

Abstract

Industry 4.0 aims at providing a digital representation of a production landscape, but the challenges in building, maintaining, optimizing, and evolving digital models in inter-organizational production chains have not been identified yet in a systematic manner. In this paper, various Industry 4.0 research and technical challenges are addressed, and their present scenario is discussed. Moreover, in this article, the novel concept of developing experience-based virtual models of engineering entities, process, and the factory is presented. These models of production units, processes, and procedures are accomplished by virtual engineering object (VEO), virtual engineering process (VEP), and virtual engineering factory (VEF), using the knowledge representation technique of Decisional DNA. This blend of the virtual and physical domains permits monitoring of systems and analysis of data to foresee problems before they occur, develop new opportunities, prevent downtime, and even plan for the future by using simulations. Furthermore, the proposed virtual model concept not only has the capability of Query Processing and Data Integration for Industrial Data but also real-time visualization of data stream processing.     

Deployment of a cloud pipeline for real-time visual inspection using fast streaming high-definition images

We investigate the challenges of building an end-to-end cloud pipeline for real-time intelligent visual inspection system for use in automotive manufacturing. Current methods of visual detection in automotive assembly are highly labor intensive, and thus prone to errors. An automated process is sought that can operate within the real-time constraints of the assembly line and can reduce errors. Components of the cloud pipeline include capture of a large set of high-definition images from a camera setup at the assembly location, transfer and storage of the images as needed, execution of object detection, and notification to a human operator when a fault is detected. The end-to-end execution must complete within a fixed time frame before the next car arrives in the assembly line. In this article, we report the design, development, and experimental evaluation of the tradeoffs of performance, accuracy, and scalability for a cloud system.     

The Critical Role of Passive Permeability in Designing Successful Drugs

Passive permeability is a key property in drug disposition and delivery. It is critical for gastrointestinal absorption, brain penetration, renal reabsorption, defining clearance mechanisms and drug-drug interactions. Passive diffusion rate is translatable across tissues and animal species, while the extent of absorption is dependent on drug properties, as well as in vivo physiology/pathophysiology. Design principles have been developed to guide medicinal chemistry to enhance absorption, which combine the balance of aqueous solubility, permeability and the sometimes unfavorable compound characteristic demanded by the target. Permeability assays have been implemented that enable rapid development of structure-permeability relationships for absorption improvement. Future advances in assay development to reduce nonspecific binding and improve mass balance will enable more accurately measurement of passive permeability. Design principles that integrate potency, selectivity, passive permeability and other ADMET properties facilitate rapid advancement of successful drug candidates to patients.     

Measurement of Electrophysiological Signals In Vitro Using High-Performance Organic Electrochemical Transistors

Biological environments use ions in charge transport for information transmission. The properties of mixed electronic and ionic conductivity in organic materials make them ideal candidates to transduce physiological information into electronically processable signals. A device proven to be highly successful in measuring such information is the organic electrochemical transistor (OECT). Previous electrophysiological measurements performed using OECTs show superior signal-to-noise ratios than electrodes at low frequencies. Subsequent development has significantly improved critical performance parameters such as transconductance and response time. Here, interdigitated-electrode OECTs are fabricated on flexible substrates, with one such state-of-the-art device achieving a peak transconductance of 139 mS with a 138 µs response time. The devices are implemented into an array with interconnects suitable for micro-electrocorticographic application and eight architecture variations are compared. The two best-performing arrays are subject to the full electrophysiological spectrum using prerecorded signals. With frequency filtering, kHz-scale frequencies with 10 µV-scale voltages are resolved. This is supported by a novel quantification of the noise, which compares the gate voltage input and drain current output. These results demonstrate that high-performance OECTs can resolve the full electrophysiological spectrum and suggest that superior signal-to-noise ratios could be achieved in high frequency measurements of multiunit activity.     

Macrophage Immunomodulation Through New Polymers that Recapitulate Functional Effects of Itaconate as a Power House of Innate Immunity

Itaconate (ITA) is an emerging powerhouse of innate immunity with therapeutic potential that is limited in its ability to be administered in a soluble form. A library of polyester materials that incorporate ITA into polymer backbones resulting in materials with inherent immunoregulatory behavior is developed. Harnessing hydrolytic degradation release from polyester backbones, ITA polymers result in the mechanism specific immunoregulatory properties on macrophage polarization in vitro. In a functional assay, the polymer-released ITA inhibits bacterial growth on acetate. Translation to an in vivo model of biomaterial associated inflammation, intraperitoneal injection of ITA polymers demonstrate a rapid resolution of inflammation in comparison to a control polymer silicone, demonstrating the value of sustained biomimetic presentation of ITA.     

Social Support and Social Strain Among Husbands and Wives: A Multilevel Analysis.

In response to recent calls in the literature for within-person examinations of social support processes over time, this study explores the relationships of spousal support, spousal strain, and well-being among husbands and wives, both within the same day and across days. Eighty-three couples were interviewed and completed a structured diary twice daily for 1 week. The results of multilevel hierarchical modeling suggest that both spousal support and spousal strain made significant, independent contributions to concurrent negative affect, although only spousal support was a significant predictor of next-day negative affect. Spousal strain interacted with spousal support to predict next-day negative affect. Direct and moderating effects of perceived marital adjustment on negative affect were discussed. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Dual command travel times and miniload system throughput with turnover-based storage

We analyze travel times for automated storage/retrieval systems. In particular, we apply our travel time model to turnover-based storage systems and determine the mean and variance of dual command travel times. We present detailed numerical results for selected rack shape factors and ABC inventory profiles. We then investigate the effect of alternative rack configurations on travel time performance measures. We also show how to determine the throughput of miniload systems with turnover-based storage and exponentially distributed pick times.