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Building or transformation of an enterprise software system is an onerous process which requires a precise definition of business demands. Then to enable the satisfaction of business requirements, the well-thought-of and convenient software architecture must be determined and designed. According to common sense, there are two methods to be followed in order to find the right solution for a problem. One is to handle the problem as a whole; like the traditional monolith architecture. The second method is to divide the problem into easily understandable and soluble fine-grains. If the second path is chosen in the software world, microservices architecture can be shown. When the entire enterprise-level system design is considered, to the best of our knowledge, there is no any leading empirical research on the evaluation of software architectures, selection of communication protocol, data formats, and database. In this paper, an easily scalable, maintainable, highly-available, reliable and observable software system is designed by comparing variant architectures, communication methods, and data models that would help to choose the most appropriate architecture or model for the right purpose. All the paper is about designing a backend API system. The client types or technologies are out of scope., Kurumsal bir yazılım sisteminin oluşturulması veya dönüşümü, iş ihtiyaçlarının tam olarak tanımlanmasını gerektiren meşakkatli bir işlemdir. İş gereksinimlerinin karşılanabilmesi için iyi düşünülmüş, uygun yazılım mimarisi kararlaştırılmalı ve tasarlanmalıdır. Genel olarak sorunlara çözüm bulmak için takip edilebilecek iki yöntem vardır. Birincisi geleneksel monolitik mimaride olduğu gibi problemi, doğru çözümü bulmak için bir bütün olarak ele almaktır. İkincisi ise problemi daha kolay anlaşılabilen ve çözülebilen küçük parçalara ayırmaktır. Eğer yazılım dünyasında ikinci yöntem takip edilecek olursa, mikroservis mimarisi gündeme gelmektedir. Kurumsal ölçekli yazılım sistemi tasarlanmak istendiğinde, bildiğimiz kadarıyla yazılım mimarilerini değerlendiren, iletişim protokolü, veri modeli ve veritabanının seçimi üzerine yol gösterici deneysel bir araştırma bulunmamaktadır. Bu makalede, kolay ölçeklenebilir, bakım yapılabilir, erişilebilirliği yüksek, güvenilir ve gözlemlenebilir mikroservis tabanlı bir yazılım sistemi tasarlanmıştır. Ayrıca amacına uygun yazılım mimarisi ve modellerini seçmeye yardımcı olabilecek şekilde farklı mimarilerin, iletişim protokollerinin ve veri modellerinin karşılaştırıldığı deneysel çalışmalar sunulmuştur. Tüm makale sadece sunucu servis tasarımı ile ilgili olup istemci tipi ve teknolojileri bu çalışmanın kapsamı dışındadır.

Software Architectural Smells (SA smells) are design problems in the internal structure and behavior of an SA. These can be seen as a specific category under the umbrella concept of Technical Debt (TD). TD is a central concept in software development projects and having the means to detect and measure the smells is important to understand impairments they may cause. However, TD is only limited to the technical aspects and does not describe smells found on an enterprise level. Enterprise Architecture Debt (EAD) expands the concepts of TD beyond the technical aspects such that it covers the debts that can be found in all layers of an Enterprise Architecture (EA). EA smells give a measurement for EAD, by providing means for detecting the smell, hence enabling a method to quantify the level of debt. The goal of this paper is to find EA smells derived from existing SA smells. This has resulted in three new EA smells that could be used as measurements for the quality of an EA. They can also be used in the future as a basis for automatic EA smell detection.

The main challenge for security information and event management (SIEM) is to find critical security incidents among a huge number of false alerts generated from separate security products. To address the alert fatigue problem that is common for security experts operating the SIEM, we propose a new alert screening scheme that leverages artificial intelligence (AI)-assisted tools to distinguish actual threats from false alarms without investigating every alert. The proposed scheme incorporates carefully chosen learning algorithms and newly designed visualization tools to facilitate speedy alert analysis and incident response. The proposed scheme is evaluated on an alert dataset collected in the security operation center of an enterprise. With a recall rate of 99.598% for highly critical alerts and a false positive rate of 0.001% reported, the proposed scheme demonstrated very promising potential for real world security operations. We believe the proposed scheme is effective in addressing the alert fatigue problem, and therefore paves the way for a consolidated security solution for network security at the enterprise level.

The never-ending menace of botnet is causing many serious problems on the Internet. Although there are significant efforts on detecting botnet at the global level which rely heavily on finding failed queries and domain flux information for botnet detection, there are very few efforts being made to detect bot infection at an enterprise level. Detecting bot-infected machines is vital for any organization in combating various security threats. This work proposes a novel anomaly-based detection technique which considers hourly hosts DNS fingerprint and attempts to find anomalous behavior which is quite different from normal machine behavior. This work successfully demonstrates the DNS Anomaly Detection (named BotDAD) technique for detecting bot-infected machine in a network using DNS fingerprinting.

Agent paradigm is a technology recognized as potent tool for the 21st century manufacturing system. Researches are ongoing in the applications of agent technology to manufacturing enterprise, production process planning and scheduling, shop floor control, and to reconfigurable manufacturing system as an implementation case study. The article presents the results of a review of published articles on agents’ usage at manufacturing enterprise level for reconfigurable manufacturing system between year 2008 and 2018 to provide up to date pictures of the technological function of agents and multi agents within the reconfigurable conceptualized manufacturing circles. The paper is view from the angle of wide coverage, broad scope of multi-agent techniques and a focus on real world applications. The outcomes include behavioral pattern and trends of agents and multi-agent’s usage in manufacturing enterprise resource planning and supply chain managements, the gaps yet to be fill for consolidating future on industry 4.0 in reconfigurable manufacturing system, and development of mobile apps interacting platform for IoT real time database communication and coordination for RBPM controller agents.

In the article the basic directions of development of innovative activity at mega- and microlevels are considered. The key tasks of scientific and technical policy have been studied with the purpose of determining the most effective innovation strategy that allows introducing the latest technologies into production. The main means for successful development of an enterprise in uncertain and rapidly changing environmental conditions is an effective integrated approach that ensures the formation and implementation of such an innovative activity option that will ensure the best results in the current situation. In these conditions, along with the important role of the production, resource and technological potential of the enterprise, the synergetic effect becomes crucial. The proposed methodology for determining the synergistic effect will link the directions of development of innovation activity using four groups of indicators (equipment, technology, management, sales). It is universal by definition not only of certain directions and projects at the enterprise level, but can be used at the level of the region and the country.

Despite its widespread use in consumer devices and enterprise storage systems, NAND flash faces a growing number of challenges. While technology advances have helped to increase the storage density and reduce costs, they have also led to reduced endurance and larger block variations, which cannot be compensated solely by stronger ECC or read-retry schemes but have to be addressed holistically. Our goal is to enable low-cost NAND flash in enterprise storage for cost efficiency. We present novel flash-management approaches that reduce write amplification, achieve better wear leveling, and enhance endurance without sacrificing performance. We introduce block calibration, a technique to determine optimal read-threshold voltage levels that minimize error rates, and novel garbage-collection as well as data-placement schemes that alleviate the effects of block health variability and show how these techniques complement one another and thereby achieve enterprise storage requirements. By combining the proposed schemes, we improve endurance by up to 15× compared to the baseline endurance of NAND flash without using a stronger ECC scheme. The flash-management algorithms presented herein were designed and implemented in simulators, hardware test platforms, and eventually in the flash controllers of production enterprise all-flash arrays. Their effectiveness has been validated across thousands of customer deployments since 2015.

Risk Assessment contributes to optimizing the allocation of resources at the enterprise level, which achieves its goals, so the matter needs centralized management of risks on the enterprise level, not for each project. The risk assessment is carried out through several stages and by using various methods. This research provides an analytical view of risk assessment in concurrent multiple software projects environment. Research experiment has proven high levels of accuracy, reaching almost from 93% by using Simple Logistic into 98% using REP Tree technique. in determining risk levels in a concurrent multi-project environment.

Whether you're a newbie or an expert in the programming space, you must have wondered one way or the other how other developers set up and configure their starting project application, right?

While backtracking analysis has been successful in assisting the investigation of complex security attacks, it faces a critical dependency explosion problem. To address this problem, security analysts currently need to tune backtracking analysis manually with different case-specific heuristics. However, existing systems fail to fulfill two important system requirements to achieve effective backtracking analysis. First, there need flexible abstractions to express various types of heuristics. Second, the system needs to be responsive in providing updates so that the progress of backtracking analysis can be frequently inspected, which typically involves multiple rounds of manual tuning. In this paper, we propose a novel system, APTrace, to meet both of the above requirements. As we demonstrate in the evaluation, security analysts can effectively express heuristics to reduce more than 99.5% of irrelevant events in the backtracking analysis of real-world attack cases. To improve the responsiveness of backtracking analysis, we present a novel execution-window partitioning algorithm that significantly reduces the waiting time between two consecutive updates (especially, 57 times reduction for the top 1% waiting time).

The web of the IoT has been started but also had some serious issues related to its security. It doesn't matter to what level its vulnerability affects. It can be domestic or any enterprise level. Billions of devices are linked with the internet. It is the network of objects and sensors by which these devices exchange data with each other without human involvement. On a large scale, there is a struggle to protect data from leaking. The main purpose of this is to review the survey of the work done in security in the specific area. As a whole, this study is measuring the flaws in the security related to the Internet of Things. Design and Protocols are studied in this survey for securing the communications between so-called ‘things'. Open inspection problems and security application challenges in IoT security are still present. This study is aimed to be a helpful guidebook to learn the vulnerabilities and threats related to security in IoT and increases the security design.

Enterprise networks are large, complex, and typically organized along enterprise lines. While RIP is fine for smaller networks, at the enterprise level RIP becomes very problematic. In some cases, RIP updates can comprise more than 25% of the network traffic.

With the continuous expansion of operation monitoring business, the refinement of data mining needs and the increasing precision of management services in power enterprises, new requirements have been put forward for business management and data management in power enterprises. Traditional business management and data management can no longer meet the requirements of large data mining analysis. There is an urgent need to speed up the construction of enterprise-level business and data fusion data analysis service platform. This paper analyses the background, objectives and ideas of platform construction in detail, and introduces the implementation scheme of enterprise-level business and data fusion data analysis service platform based on big data technology, including the overall architecture design, construction content, etc. The construction of enterprise-level business and data fusion data analysis service platform has important research significance and application value for improving the level of operation and management in an all-round way.

Online controlled experiments, known as A/B tests, have delivered tremendous value for businesses and customers. Traditionally, online controlled experiments running in search engines, websites, mobile apps, and other Business-to-Consumer (B2C) products use individual customers as randomization units. However, this may not be possible in Business-to-Business (B2B) products that are sold to, and used by, other enterprises. B2B products typically have constraints such as the need to provide identical experiences to all users within an enterprise. In other scenarios, such as features that need to be used by multiple users to be meaningful or the metrics of interest can be only obtained by showing the same experience under one enterprise, experimentation randomized by enterprise is needed. In this paper, based on experiences from Microsoft and Outreach, we introduce the concept of Enterprise Level Experiments (ELE) in software product development. We discuss the unique technical challenges in designing and analyzing ELEs and present solutions to overcome them. Furthermore, we present and discuss a real-world example of ELE run by Microsoft. Our aims in this paper are to provide practical guidance on running trustworthy experiments in B2B scenarios, and to stimulate further research in this new and important area of experimentation.

The manufacturing industry has now started the 4th revolution; also referred to as Industry 4.0, powered by the Industrial Internet of Things (IIoT) technology. In this context factories are now being transformed into smart industries by automation of the Shop Floors. Automation comprises of scheduling and monitoring cycles. To implement the true essence of Industry 4.0, several different techniques have been applied to schedule the shop floor tasks, while a gap persists in monitoring the Job Shop Scheduler. This paper aims at presenting an optimized IIoT based Job Shop Scheduler Monitoring System that tracks the tasks being performed by the machines, thus completing the closed loop feedback path, enabling automatic detection of completion time of a job and based on that, dynamic rescheduling. This automation improves the efficiency of the whole shop floor and ultimately resulting in the optimal management of the resources and time at enterprise level. The monitoring system was tested in an actual shop floor setting and results verify the practicability in improving performance of the shop floor.

Industrial automation networks are composed of cyber-physical systems where frame delays and jitter influence significantly the quality of communication between control and field devices. Due to these constraints, such systems are often served by dedicated Fieldbus networks which are different from networks for enterprise-level connectivity. However, with the introduction of Time-sensitive Networking standards which are already integrated into IEEE 802.1Q-2018 standards in essential parts, the long expected single converged network for any-type communication in the field, control, and enterprise level is within reach. With it, comes the challenge of synthesizing schedules to obtain parameters for configuring the network bridges for time-triggered communication services.This paper provides a scheduling verification, and Gate Control event computation algorithm focused on asserting the viability of scheduling communication services for multiple independent periodic Talker applications on IEEE 802.1Q- Time Sensitive Networks as well as the computation of Gate Control Lists for the bridges.

Within the recent decade, major innovations in technology have emerged, that potentially add more convenience to daily life practices not only on an enterprise level but on an individual level as well. Cloud Computing technology has witnessed significant advances in its implementation and become widely adopted by either private or public sectors. It was obvious recently that a lot of organizations and enterprises are transferring their workloads to the cloud. However, security is a major concern for the cloud computing services which is based on Internet connection that makes it vulnerable to multiple types of attacks. Even though that the security measures implemented over cloud computing are developing every passing year, Security still a challenge. In this paper, we conducted a survey study on cloud computing and addressed different types of attacks and possible threats to this emerging technology, as well as protection methods and existing solutions to such attacks.

The third wave of informatization marked by cloud computing, Internet of Things, and big data is coming. The application of informatization is expanding from the enterprise level to the social level. The enterprises will face the reconstruction of computing platforms and information platforms, as well as the reconstruction of enterprise operation management models and business models. This article conducts extensive surveys and statistics on the application of XBRL financial reports under the big data environment from the two dimensions of the supervisory level and the enterprise, and conducts visual analysis and in-depth discussion, in order to use big data technology to improve the quality of XBRL financial report submission information.

This paper proposes an enterprise-level document management system integration solution, which can effectively solve the problems of the coexistence of multiple document management systems in enterprises and public institutions, the repeated collection of document data and the inefficient access application. The solution also can effectively support the data security and confidentiality of enterprises and public institutions. The core idea of the integration solution is to realize the application integration between the document integration application system and the document information management systems by taking the document classification collection management regulations as the management basis, taking the document information integration application system as the technical carrier, and adopting the SOA technology. The integration solution has been proved to be effective in practice, with significant application value and promotion value.

This system is an Enterprise-Level information sharing platform based on browser/server mode (B/S), page frame stand tools in hypertext preprocessor language package. It consists of the user management module, file management module, friend’s management module, information management module and administrator module. The system can provide in LAN users to more quickly and more convenient to share pictures, file upload and download, and make them in the Internet which is not restricted by time and space. Through the implementation of the system, the information exchange between users is promoted, the user’s free access is realized, the operation becomes simpler, the efficiency of information interaction between the employees of the enterprise is improved, and the work efficiency is improved.

In modern mining, it is imperative to have a real-time flow of information between enterprise level systems (ERP, CRM, SCM) and shop floor systems. The gaps that exist between the two spheres make it difficult for managers to have timely information for optimum decision making. A mining company needs instantaneous visibility on production, quality, cycle times, machine status, and other important operational variables in order to achieve optimum and effective operations. With the implementation of Industry 4.0 technologies fragmented shop floor systems and the enterprise level systems communicate seamlessly in delivering optimum operations. The research demonstrates Industry 4.0 technologies as the mechanisms for integrating business systems and processes. The methods researched are deployed in a uranium mining company to integrate all shop floor systems with SAP ERP. The results introduce a semi-smart Mine with real-time visibility of overall mining status.

Decision-making within a complex operating environment spanning multiple domains necessitates enterprise-level operational agility. In this case, operational agility involves ability to react to dynamic opponents and the orchestration of technical resources as well as alignment of managerial processes. A shift from the system level to the enterprise view is necessary. However, there is a lack of frameworks addressing how operational agility at the enterprise level can be obtained. The aim of this study was two-fold: (i) to understand the concept of operational agility in context of recent developments and their challenges, and (ii) to propose an innovative metric feeding into operational agility as the enterprise level. Our results indicate that current commonly used systems engineering metrics focus on system specific measures of merit. In this research, we suggest new metrics to enable system/capability evaluation with an enterprise or portfolio context-the enterprise readiness level. A research path forward is proposed.

In this chapter we explore the application of MBSAP to the organizational level of an enterprise or system-of-systems (SoS), the highest level of the structural hierarchy. Enterprise architecture raises a number of new challenges because the individual systems that make up the enterprise are often developed, managed, and operated independently, making it difficult to harmonize their interactions. A fully satisfactory System-of-Systems Engineering (SoSE) methodology does not yet exist, but a number of useful approaches are available that can be incorporated into MBSAP. We first discuss general considerations of enterprise architectures and then focus on the technical challenges, which we approach by considering the enterprise as a system-of-systems (SOS), including a brief look at adaptive and emergent behavior, which can be especially significant in an enterprise context. With this background established, we introduce the extension of MBSAP for enterprise architecture and further develop this in an SoSE methodology. The remainder of the chapter addresses specific aspects of SoSE, including interoperability among systems within an SoS, modeling and simulation at the enterprise level, enterprise networking, and dynamic enterprises. Chapter Objective: the reader will be able to apply MBSAP, with appropriate extensions, to deal with the challenges of an SoS and create effective enterprise architectures that are open, robust, and evolvable.

The objective of the Honeypot security system is a mechanism to identify the unauthorized users and intruders in the network. The enterprise level security can be possible via high scalability. The whole theme behind this research is an Intrusion Detection System and Intrusion Prevention system factors accomplished through honeypot and honey trap methodology. Dynamic Configuration of honey pot is the milestone for this mechanism. Eight different methodologies were deployed to catch the Intruders who utilizing the unsecured network through the unused IP address. The method adapted here to identify and trap through honeypot mechanism activity. The result obtained is, intruders find difficulty in gaining information from the network, which helps a lot of the industries. Honeypot can utilize the real OS and partially through high interaction and low interaction respectively. The research work concludes the network activity and traffic can also be tracked through honeypot. This provides added security to the secured network. Detection, prevention and response are the categories available, and moreover, it detects and confuses the hackers.

•FAA estimates the impacts of changes in the NAS — using a fast-time simulation called the System-wide Analysis Capability (SWAC) — simulated for future years, based on historical flight plans and TAF growth Objective: — Investigate UAS current and future traffic in the NAS — Incorporate UAS flights into the SWAC simulation in order to include their impact on NAS operations — Support enterprise level analyses of technologies to integrate UAS demand into NAS operations.

This paper presents an approach to evaluate sustainable manufacturing performance at line, plant and enterprise levels. First, requirements for a sustainable manufacturing evaluation framework are identified through reviewing existing literature. A framework to concurrently consider the three pillars of sustainability, total life-cycle emphasis, and 6R (reduce, reuse, recycle, recover, redesign and remanufacture) concept is then developed. The framework is used to propose index-based methods for sustainable manufacturing performance evaluation. Metrics for economic, environmental and societal performance measurement are progressively aggregated to determine performance at sub-cluster, cluster, sub-index, index levels. The proposed approach allows to integrate metrics relevant to product and process performance to evaluate systems level sustainable manufacturing from the line to plant to enterprise level. The application of the proposed approach is illustrated using two examples.

Today, a number of technologies are available for building of Big Data architecture deciding which technology will provide the maximum value out of the architecture depending on the extensive study of the present architecture in use, the type of data being ingested, and the desired value expected by the enterprise. In this research paper, we highlight Big Data and its characteristic, Big Data architect, various technologies involved at different levels, pipeline architecture of Big Data architecture, technologies used, planning and designing, and challenges faced while building Big Data architecture at enterprise scale.

While the previous chapters focused on the technical configurations of deploying a SharePoint farm using modern tooling and practices, it is important to be able manage these processes at an enterprise level. Proper access control, automation, and workflow are instrumental in ensuring that these practices can scale and meet the demand of an ever-changing organization. Following are some industry standards and best practices that can enable your team and organization.

This paper examines human and social factors of production innovations. An assessment method is proposed to be used for various purposes at the enterprise level. The method is built upon a theoretically justified model that relates human and social endowments to the production innovations as well as the outcomes. The approach derives from the resource based viewing of a strategy process. The holism of assessment is assured by the consideration of crucial interdependencies, the consistency of assessment and the integrity of assessment.

Most enterprises generate a huge amount of public and private dataset actively with the integration of modern technology. So, security is a big concern of these dataset. Initially the security is provided at enterprise level but now-a-days it is an inevitable task to provide security at personal level. So to achieve the security generalization, suppression, slicing and one attribute per column slicing is used till now. The aim of this paper is to draw a review of all the existing techniques which are used in privacy preservation with comparative analysis of all anonymization techniques and show the flaw of privacy preservation techniques with respect to different parameters.

Knowledge management (KM) is recognized as contributing significantly to the organizational performance. Researchers have worked hard on KM performance measurement on the enterprise level. They investigate KM performance determinants and provide numerous KM performance models. Meanwhile, little research has been undertaken to assess knowledge management projects performance. In fact, the growing number of KM project confirms the need for a performance measurement model, able to assess, each time a KM project is introduced, the performance of such project in order to rationalize its use, evaluate its effectiveness and justify its consequent financial costs.

An enterprise-level #exible manufacturing approach for a multi-product manufacturer like an automotive company requires a cost-e4ective mix of many key enablers, including #exible assembly plants, part commonality between products, and supply base #exibility. This paper develops a strategic planning model that determines the overall business value of #exible manufacturing systems. The model is designed to be capable of dealing with problems of realistic size and scope. Interpretation of results of the model gives important strategic insights on factors in#uencing manufacturing #exibility and capacity requirements in the presence of these factors. The model is applied to study a #exibility evaluation problem faced by a major automotive company. The experimental results show that #exibility enablers such as #exible product to manufacturing facility assignments and part commonality can lead to improved pro"tability. Increases in pro"tability of up to 17% (? $300 M=year) are seen in the modeled system. Increased commonality and/or #exibility also result in a reduction of the optimal capacity for the assembly system while simultaneously slightly improving sales. These results are robust with respect to introduction of the regulatory compliance issue of fuel economy standards, although the incremental pro"ts from improved #exibility and commonality are reduced by approximately 25% when fuel economy standards are included. ? 2004 Elsevier Ltd. All rights reserved.

Agile has been in the limelight for well over a dozen years. Agile has secured its place within the software development community and now it is spreading into many other areas of business where the incremental nature and promise of better business outcomes are very tantalizing. Many people are realizing that a more iterative approach allows them the flexibility to adapt to the changing needs of customers and the continuous churning of the marketplace. Others would like to apply Agile because they are hearing about it from all corners of their professional life and think maybe its time to get on the bandwagon. For many reasons, there are real benefits that can be derived from applying Agile.

The fast evolving Big Data Tools and Platforms space has given rise to various technologies to deal with different Big Data use cases. However, because of the multitude of the tools and platforms involved it is often difficult for the Big Data practitioners to understand and select the right tools for addressing a given business problem related to Big Data. In this chapter we cover an introductory discussion to the various Big Data Tools and Platforms with the aim of providing necessary breadth and depth to the Big Data practitioner so that they can have a reasonable background to start with to support the Big Data initiatives in their organizations. We start with the discussion of common Technical Concepts and Patterns typically used by the core Big Data Tools and Platforms. Then we delve into the individual characteristics of different categories of the Big Data Tools and Platforms in detail. Then we also cover the applicability of the various categories of Big Data Tools and Platforms to various enterprise level Big Data use cases. Finally, we discuss the future works happening in this space to cover the newer patterns, tools and platforms to be watched for implementation of Big Data use cases.

For many applications, performance is paramount. For example, to improve conversion rates in e-commerce applications or to comply with service level agreements. Current trends in enterprise level architecture focus on designing and orchestrating services. These services are typically designed to be functionally isolated from each other up to a certain degree. During the design phase as well as when the application is deployed, choices have to be made how services interact and where they need to be deployed. These choices have a profound impact on the responsiveness of an application as well as on which performance can be made. In this paper we propose a methodology to describe and analyse performance dependencies between services. The resulting model can then be used to assist in designing a service oriented architecture and improving existing solutions by pointing out performance dependencies of services.

In 2007 we presented a paper that described the application of Natural Language Processing (NLP) and Machine Translation (MT) for the automated translation of process build instructions from English to other languages to support Ford’s assembly plants in non-English speaking countries. This project has continued to evolve with the addition of new languages and improvements to the translation process. However, we discovered that there was a large demand for automated language translation across all of Ford Motor Company and we decided to expand the scope of our project to address these requirements. This paper will describe our efforts to meet all of Ford’s internal translation requirements with AI and MT technology and focus on the challenges and lessons that we learned from applying advanced technology across an entire corporation.

International audience; In this paper we discuss the creation of an information centric framework to develop a virtual reality environment for micro surgery. An information model of micro surgery was built through interactions with an expert micro surgeon using the engineering Enterprise Modeling Language (eEML). The overall approach and architecture of the micro surgical environment is discussed. An enterprise level surgical manager, surgical planner and other components work together to enable the functioning of the virtual environment for micro surgery. Such virtual environments are essential to educating / training young budding surgeons..

A global industrial enterprise is a complex network of different distributed production plants producing, inventory, and distributing products. Agent-based model provides the approach to prove complex network problems of independent actors. A global economy and increase in both demand fluctuation and pressures for cost decreasing while satisfying customer services have put a premium on smart supply chain management. It is important to make risk-benefit analysis of supply chain design alternatives before making a final decision. Simulation gives us an effective approach to comparative analysis and evaluation of the alternatives. In this paper, we describe an agent-based simulation tool for designing smart supply chain networks as well logistic networks. Using an agent-based approach, supply chain models are composed from supply chain agents. The agent-based simulation tool can be very useful for predicting the effects of local and system-level activities on multi-plant performance and improving the tactical and strategic decision-making at the enterprise level. Specifically, this model can reveal the optimal method to ship the inventory on some situations which are demand fluctuation and network disruption. The demand fluctuation effects the inventory management. The network disruption restricts the logistics. This model evaluates supply chain management from the viewpoints of the amount of inventory, the way of shipping and cost.

In this position paper we present the Automagic Box of Beauty, a prototype smart cabinet which enables the user to track their rate of consumption of toiletries. By transmitting product consumption data from the box to the Hub-of-all-Things (HAT), a platform for personal data that is fully owned and controlled by the individual, we open the potential for decision support for the user that hitherto has only been available at the enterprise level. By returning ownership of personal data to the individual, the HAT enables horizontal integration of information that has until now been held in vertical silos. We show how, by contextualizing the product consumption data with data from a variety of other sensors and sources, the system will support individual users in making decisions – in this use case example, decisions about replenishment and selection of the products in the box.

The previous chapter delineated the constraints and goals of the presented research work. The goals should fulfill the criteria of a good PMS—comprehensive, causally oriented, vertically integrated, horizontally integrated, internally comparable and useful [17]. Subsequently, it is crucial to exploit inter-disciplinary fundamentals, technologies and standards. The following content is based on extensive literature review of books, journal articles, conference articles, standards, and whitepapers, and interaction with numerous experts.