STEP-NC based high-level machining simulations integrated with CAD/CAPP/CAM

With the development of manufacturing,numerical control(NC) machining simulation has become a modern tool to obtain safe and reliable machining operations.Although some research and commercial software about NC machining simulations is available,most of them is oriented for G&M code.It is a low-level data model for computer numerical control(CNC),which has inherent drawbacks such as incomplete data and lack of accuracy.These limitations hinder the development of a real simulation system.Whereas,standard for the exchange of product data-compliant numerical control(STEP-NC) is a new and high-level data model for CNC.It provides rich information for CNC machine tools,which creates the condition for an informative and real simulation.Therefore,this paper proposes STEP-NC based high-level NC machining simulations solution integrated with computer-aided design/computeraided process planning/computer-aided manufacturing(CAD/CAPP/CAM).It turned out that the research provides a better informed simulation environment and promotes the development of modern manufacturing.     

Using views for product data exchange

Proprietary data structures complicate data sharing by making it difficult to save a product model from one software tool and load it directly into another tool. Engineers may want, for example, to verify with an analysis tool that all design constraints have been met or to prepare a design for manufacturing. In such cases, software developers must find a means of moving the product model from the proprietary data structures of a CAD system to those of the analysis system and the manufacturing system, with minimal loss of information. A database view, used in conjunction with data exchange standards, can facilitate the sharing of product model data between software tools in design and manufacturing computing environments     

Process-data-warehousing-based operator support system for complex production technologies

Process manufacturing is increasingly being driven by market forces, customer needs, and perceptions, resulting in more and more complex multiproduct manufacturing technologies. The increasing automation and tighter quality constraints related to these processes make the operator's job more and more difficult. This makes decision support systems (DSSs) for the operator more important than ever before. A traditional operator support system (OSS) focuses only on specific tasks that are performed. In the case of complex processes, the design of an integrated information system is extremely important. The proposed data-warehouse-based OSS makes possible linking complex and isolated production units based on the integration of the heterogenous information collected from the production units of a complex production process. The developed OSS is based on a data warehouse designed by following the proposed focus-on-process data-warehouse-design approach, which means stronger focus on the material and information flow through the entire enterprise. The resulting OSS follows the process through the organization instead of focusing separate tasks of the isolated process units. For human-computer interaction, front-end tools have been worked out, where exploratory data analysis and advanced multivariate statistical models are applied to extract the most informative features of the operation of the technology. The concept is illustrated by an industrial case study, where the OSS is designed for the monitoring and control of a high-density polyethylene (HDPE) plant.     

Outlier detection in audit logs for application systems

An outlier is defined as an observation that is significantly different from the other data in its set. An auditor will employ many techniques, processes and tools to identify these entries, and data mining is one such medium through which the auditor can analyze information. The enormous amount of information contained within transactional processing systems׳ logs means that auditors must employ automated systems for anomalous data detection. Several data mining algorithms have been tested, especially those that deal specifically with classification and outlier detection. A group of these previously described algorithms was selected for use in designing and developing a process to assist the auditor in anomalous data detection within audit logs. We have been successful in creating and ratifying an outlier detection process that works in the alphanumeric fields of the audit logs from an information system, thus constituting a useful tool for system auditors performing data analysis tasks.     

Visualization of multivariate data with radial plots using SAS

Data visualization tools can provide very powerful information and insight when performing data analysis. In many situations, a set of data can be adequately analyzed through data visualization methods alone. In other situations, data visualization can be used for preliminary data analysis. In this paper, radial plots are developed as a SAS-based data visualization tool that can improve one's ability to monitor, analyze and control a process. Using the program developed in this research, we present two examples of data analysis using radial plots; the first example is based on data from a particle board manufacturing process and the second example is a business process for monitoring the time-varying level of stock return data.     

制氧过程实时监控系统的设计与实现

制氧过程实时监控系统针对气体厂地域分布比较广,生产点多,在不同时期应用了多套不同的控制系统的情况,提出了通过OPC协议进行信息集成的方案。制氧过程实时监控系统完成了全厂的数据采集,提供流程图、趋势图、生产报表等多种画面监控分析工具,提高了调度的水平,增加了气体的产量。     

Evaluation of techniques for manufacturing process analysis

In the last 20 years, several methodologies, models and tools have been developed for the analysis and optimisation of manufacturing systems in order to propose general improvements. Many of these techniques make extensive use of data modelling, simulation, decision-making support, expert systems and reference models. This paper presents the first outcome of a piece of research work to integrate manufacturing process analysis into an integrated modelling framework covering all aspects related to the shop-floor as it really is. The main methodologies and software tools have been identified and evaluated and the results tested on industrial examples. As a result of this evaluation it has been possible to identify the inefficiencies of the techniques. These problems are connected with integrating the different types of data to be analysed—such as quality, time, costs, resource capacity, productivity, flexibility or improvements—into a single analysis environment. The inefficiencies detected enable us to present a general framework for making better use of modelling techniques for manufacturing process analysis. Received July 2005 / Accepted January 2006     

Composing domain-specific design environments

Domain-specific integrated development environments can help capture specifications in the form of domain models. These tools support the design process by automating analysis and simulating essential system behavior. In addition, they can automatically generate, configure, and integrate target application components. The high cost of developing domain-specific, integrated modeling, analysis, and application-generation environments prevents their penetration into narrower engineering fields that have limited user bases. Model-integrated computing (MIC), an approach to model-based engineering that helps compose domain-specific design environments rapidly and cost effectively, is particularly relevant for specialized computer-based systems domains-perhaps even single projects. The authors describe how MIC provides a way to compose such environments cost effectively and rapidly by using a metalevel architecture to specify the domain-specific modeling language and integrity constraints. They also discuss the toolset that implements MIC and describe a practical application in which using the technology in a tool environment for the process industry led to significant reductions in development and maintenance costs     

A method of NC machine tools intelligent monitoring system in smart factories

The construction of effectual connection to bridge the gap between physical machine tools and upper software applications is one of the inherent requirements for smart factories. The difficulties in this issue lies in the lack of effective and appropriate means for real-time data acquisition, storage and processing in monitoring and the post workflows. The rapid advancements in Internet of things (IoT) and information technology have made it possible for the realization of this scheme, which have become an important module of the concepts such as “Industry 4.0”, etc. In this paper, a framework of bi-directional data and control flows between various machine tools and upper-level software system is proposed, within which several key stumbling blocks are presented, and corresponding solutions are subsequently deeply investigated and analyzed. Through monitoring manufacturing big data, potential essential information are extracted, providing useful guides for practical production and enterprise decision-making. Based on the integrated model, an NC machine tool intelligent monitoring and data processing system in smart factories is developed. Typical machine tools, such as Siemens series, are the main objects for investigation. The system validates the concept and performs well in the complex manufacturing environment, which will be a beneficial attempt and gain its value in smart factories.     

Extending Security Protocol Analysis: New Challenges

We argue that formal analysis tools for security protocols are not achieving their full potential, and give only limited aid to designers of more complex modern protocols, protocols in constrained environments, and security APIs. We believe that typical assumptions such as perfect encryption can and must be relaxed, while other threats, including the partial leakage of information, must be considered if formal tools are to continue to be useful and gain widespread, real world utilisation. Using simple example protocols, we illustrate a number of attacks that are vital to avoid in security API design, but that have yet to be modelled using a formal analysis tool. We seek to extract the basic ideas behind these attacks and package them into a wish list of functionality for future research and tool development.     

Design of a computerized scheduling system for best rule analysis and control

A Computerized Scheduling System (CSS) for a gear box manufacturing plant has been developed to simulate a specific manufacturing facility and to analyse conditions that identify bottlenecks during the production process. The model, based partly on practical experience and partly on theoretical work, allows the analyst to concentrate on a single entity (such as a job) and the sequence of events and activities that undergoes as it “passes through” the system. The CSS makes use of actual company data regarding individual machines and operators, and incorporates interarrival times, job types, tasks for each job, routings for the different job types and process time for each job type and specific task. Also, the model provides information on output — average total delay in queue, average number in queue, average utilization and average delay in queue. Although the resultant model was constructed for the application on hand, the principles employed can be extended to include procedures encountered in similar manufacturing environments.     

Information appliances and tools in Visage

A workspace for information analysis must support two types of analysis: routine information reporting and exploratory analysis. We have been developing a workspace called Visage to address both types of analysis tasks. Our goal is for expert users to move easily between routine tasks and exploratory data analysis as situations demand. Furthermore, recognizing the inherent complexity of data analysis, we want a system that is accessible to occasional users yet simultaneously provides power and flexibility for expert users. Ideally, such a system should support a gradual shift to increasing expertise so that occasional users of routine interfaces can perform more detailed analyses if needed. Visage addresses these needs by providing a consistent interface to a wide variety of data manipulation and visualization primitives. Plus, it lets users combine these operations to create appliances-special-purpose applications capturing multiple steps of a routine data analysis process-in a single, simple interface. Analysts thus benefit from a common set of operations and ways to integrate information across applications. Visage provides both basic tools and specialized information appliances to help them     

物理设计EDA中可扩展数据支撑系统结构

提出了一种可扩展的数据支撑系统结构,该系统为EDA物理设计工具开发提供数据支持．当设计工艺技术进入超深亚微米后,物理设计过程复杂性增加,大数据量、复杂结构的数据表示成为一个关键问题．需要提供一个有效的、可扩展的数据支撑环境,支持多层次、多迭代、结构化设计过程的集成．该数据支撑系统采用可扩展标记语言XML表示设计数据,完成设计过程大规模、多种类、多阶段数据表示和处理,提高数据系统的可扩展性．文中对该数据支撑系统结构进行了说明,结合实际集成需求,对数据表示、数据解析和数据转换等关键技术的处理也进行了详细说明．     

A hybrid methodology for restructuring decision of a manufacturing system: A case study

The output performance of a manufacturing system depends on its operational continuity. However, a manufacturing system can stop for a short time or it can be out of service for a long time due to crucial problems such as poor performance of old machines, unexpected breakdowns or faulty plant and system design. Many firms try to restructure their manufacturing systems to avoid these crucial problems and to be more efficient, profitable and better organized. However, the decision to begin the process of restructuring is a difficult and critical choice for most decision makers due to the fact that the decision threshold of the process is ambiguous. This paper proposes a hybrid methodology for the decision makers who will decide on restructuring a manufacturing system. The proposed methodology provides crucial information for the decision makers combining fuzzy logic approach and reliability analysis.     

Data driven production modeling and simulation of complex automobile general assembly plant

Flexible manufacturing and customization has long been a topic in modern manufacturing society. However, challenges still remain on the responsiveness of production system to the fluctuation of market demand. In this paper, we developed a data driven simulation methodology to automatically model a production system and rapidly modify the model corresponding to dynamic requirements and real time information. This methodology provides a “rapid prototyping” capability for production system modeling and enables a quick analyzing and remodeling capability to respond to the fluctuation of demands. The approach is developed and applied to an automotive general assembly plant with an online material handling system. A complete information model based on IDEF1X is constructed for this domain specific modeling and simulation. The main simulation modules for assembly line and material handling system of the plant floor are analyzed and a simulator is implemented in ARENA by SIMAN/VBA program. The case study of an automotive assembly plant shows that the data driven approach enables the modeling and simulation of the complex assembly plant in a “real-time” fashion and therefore effectively improve the responsiveness and flexibility of the production line.     

Querying a building information model for construction-specific spatial information

The design and construction community has shown increasing interest in adopting building information models (BIMs). The richness of information provided by BIMs has the potential to streamline the design and construction processes by enabling enhanced communication, coordination, automation and analysis. However, there are many challenges in extracting construction-specific information out of BIMs. In most cases, construction practitioners have to manually identify the required information, which is inefficient and prone to error, particularly for complex, large-scale projects. This paper describes the process and methods we have formalized to partially automate the extraction and querying of construction-specific information from a BIM. We describe methods for analyzing a BIM to query for spatial information that is relevant for construction practitioners, and that is typically represented implicitly in a BIM. Our approach integrates ifcXML data and other spatial data to develop a richer model for construction users. We employ custom 2D topological XQuery predicates to answer a variety of spatial queries. The validation results demonstrate that this approach provides a richer representation of construction-specific information compared to existing BIM tools.     

A system planning method based on templates for large-scale manufacturing information systems

In the field of manufacturing, there is a need to develop large-scale manufacturing information systems. This is especially true in the Japanese steel manufacturing industry where CIM is the core management technology. But developing such systems requires large amounts of time and manpower, and furthermore, these type of projects are very difficult to manage. Therefore, in order to ease the process of analysis and design, we propose procedures based on a two-dimensional template with specific criteria for large-scale manufacturing IS architectures. In each manufacturing system, there are two important elements that correspond to the two dimensions of the template. One is a functional category and the other is a management structure. We show here the effectiveness of applying this method to system planning of large-scale IS in one representative steel manufacturing plant.     

Dynamics of pesticide uptake into plants: From system functioning to parsimonious modeling

Dynamic plant uptake models are suitable for assessing environmental fate and behavior of toxic chemicals in food crops. However, existing tools mostly lack in-depth analysis of system dynamics. Furthermore, no existing model is available as parameterized version that is easily applicable for use in spatially resolved frameworks for comparative assessment. In the present paper, we thus analyze the dynamics of substance masses in a multi-compartment plant–environment system by applying mathematical decomposition techniques. We thereby focus on the evolution of pesticide residues in crop components harvested for human consumption by taking wheat grains as example. Results show that grains, grain surface and soil are the compartments predominantly influencing the mass evolution of most pesticides in the plant–environment system as a function of substance degradation in plant components and overall residence time in soil. Additional influences are associated with substance molecular weight and time span between pesticide application and crop harvest. Building on these findings, we provide an accurate and yet simple linear approximation of the dynamical system to predict masses in harvested crop components relative to the total applied pesticide, defined as harvest fractions. Parameterized predictions correspond well with results from the full dynamic model, with an overall deviation of a factor 22 for harvest fractions in the relevant range between 1 and 10⁻¹⁰ in wheat. The in-depth analysis of model dynamics provides additional information of the evolution of pesticides in food crops, which is important for regulators and practitioners. In addition, the parametric representation of system dynamics allows for drastically reducing input data requirements and for comparing harvest fractions of a wide range of substances without using a complex dynamic model.