基于过程模式的软件过程实施系统的柔性研究

软件过程的复杂性和不确定性要求过程实施系统具有一定的灵活性和适应动态变化的能力。基于过程模式建立了软件过程实施系统。过程模式作为过程建模的可重用组件和过程实施的可重用的知识单元．支持过程模型对软件过程动态特性的描述和定义，支持过程实施中对动态变化的处理，基于过程模式的过程实施系统具有较好的柔性。     

Agent-based intelligent system development for decision support in chemical process industry

This paper presents an agent-based intelligent system to support coordinate manufacturing execution and decision-making in chemical process industry. A multi-agent system (MAS) framework is developed to provide a flexible infrastructure for the integration of chemical process information and process models. The system comprise of a process knowledge base and a group of functional agents. Agents in the system can communicate and cooperate with each other to exchange and share information, and to achieve timely decisions in dealing with various scenarios in process operations and manufacturing management. Process simulation, artificial intelligent technique, rule-based decision supports are integrated in this system for process analysis, process monitoring, process performance prediction and operation suggestion. The implementation of this agent-based system was illustrated with two case studies, including one application in process monitoring and process performance prediction for a chemical process and one application in de-bottlenecking of a site utility system.     

支持过程度量的软件过程建模方法的研究

文章提出应从过程建模的角度考虑对过程度量的支持问题,并提出一种支持过程度量的软件过程建模方法的框架.它包括面向目标的过程度量模型建模方法、支持过程度量的软件过程描述机制的选择和支持过程度量的软件过程建模算法.     

Interactions between control and process design under economic model predictive control

Economic model predictive control (EMPC) is a model-based control scheme that integrates process control and economic optimization, which can potentially allow for time-varying operating policies to maximize economic performance. The manner in which an EMPC operates a process to optimize economics depends on the process dynamics, which are fixed by the process design. This raises the question of how process and EMPC designs interact. Works which have addressed process and control design interactions for steady-state operation have sought to simultaneously develop process designs and control law parameters to find the most profitable way to operate a process that is able to prevent process constraints from being violated and to optimize capital costs in the presence of disturbances. Because EMPC has the potential to operate a process in a transient fashion, this work first focuses on how EMPC and process design interact in the absence of disturbances. Using small-scale process examples, we seek to understand the fundamental nature of the interactions between EMPC and process design, including how these interactions can impact computational complexity of the controller and the design procedure. We subsequently utilize the insights gained to suggest controller design variables which might be considered as decision variables for a simultaneous process and control design problem when disturbances are considered.     

Complexity Measures for Process Evolution

The foundation for process evolution research is the modelling of process structural complexity. With such a model, process systems can be directed toward acquiring good maintainability attributes according to the principles of engineering. In this paper a process management (PM) model is developed to acquire directly from the target process codes the knowledge hidden among and within components of process systems. With the knowledge acquired by the PM model, process structural complexity measures in terms of partitioning, restructuring and rewriting criteria are developed; a systematic process remodularization schema is derived, and algorithms for scheduling process changes are presented. These criteria and mechanisms are used to guide the process production chain.     

Modeling Computer Forensics Process from Workflow Perspective

Similar with software process, computer forensics process is also a complex process. There have been a lot of modeling technologies for planning, analyzing and documentation of computer forensics activities. Different from software process, the step order of forensics process is very important. Skipping any step or interchanging one step may lead to the illegality of the whole forensics process, so a precise process is critical. In this paper, Petri net is used to model the computer forensics process.     

A software development process for small projects

The authors' software development process integrates portions of an iterative, incremental process model with a quality assurance process and a measurement process that is used for process improvement. Their process aims to produce high-quality and timely results with less overhead     

基于单层神经网络的流程相似性的研究

业务流程建模推荐是辅助流程建模的主要方式之一,流程相似性是该方法的核心技术,直接影响流程推荐的准确率.流程相似性包括流程图结构相似性与行为相似性两方面,为了解决流程相似性量化困难,准确率低的问题,提出基于单层神经网络的流程相似度的量化方法.对构建基于行为的流程体系,建立业务流程、独立路径、流程节点之间的函数表达关系;使...     

Intelligent adaptive process control using dynamic deadband for semiconductor manufacturing

This paper proposes an efficient control method to minimize process error and to reduce process variance in semiconductor manufacturing. The photolithography (photo) process forms a complex semiconductor circuit and is important for quality. Obstacles to the process include the facility itself, vibration, wear and tear, product/process changes and environmental influences. Control methodologies being currently used to address these issues often amplify the variation of the process by failing to perform adequate process control. Therefore, this paper proposes an effective process control method to reduce process variance by quickly detecting and identifying process disturbances and accurately reflecting the degree of change to process control. This study proposes dynamic deadband control that uses a region (band) to detect the status of a process change. It adjusts the process control based on the changes detected. In this research, the semiconductor manufacturing company is supported to perform control that is more precise and reduces fluctuations by producing products of uniform quality. In addition, it can contribute to yield due to the quality incentive and increased process control of semiconductor manufacturing.     

CMM 二级SQA 关键过程域与软件过程改进

探讨了CMM二级KPA软件质量保证的实施与软件过程改进,描述了实施SQA过程的职能、SQA过程与软件开发过程的关系和SQA过程实施。在CMM二级中,SQA是唯一评审其他5个KPA的过程域。由于它的这种监督性,软件过程改进的大部分信息源来自SQA KPA,SQA在整个软件过程的改进中起着关键的作用,充当SEPG和项目组之间的桥梁。 关键词：     

Systematic modeling and reusing of process knowledge for rapid process configuration

Rapid product development relies heavily on quick and reliable process planning and knowledge reuse. Process configuration borrows the principles of product configuration and applies them to process planning. It allows the reuse of hierarchical, historical and case-based manufacturing process knowledge to generate process plans efficiently and effectively. This paper presents a systematic knowledge model for manufacturing process cases. The model represents process knowledge at different levels of granularity and to facilitate process configuration. With this knowledge model the process knowledge is categorized into 6 levels: (i) core process skeletons, (ii) process networks, (iii) process routes, (iv) process segments, (v) processes/workplan, and (vi) operations/working step. Based on the systematic knowledge model, this paper also proposes an approach to achieve rapid process configuration by reusing the process knowledge and by performing the involved configuration rules so as to create an appropriate, reliable and effective process plan. The prototype for a graphical process planner based on this knowledge model is developed and an aerospace example is used to validate the proposed process knowledge model and process configuration.     

Stage-based discovery of business process models from event logs

An automated process discovery technique generates a process model from an event log recording the execution of a business process. For it to be useful, the generated process model should be as simple as possible, while accurately capturing the behavior recorded in, and implied by, the event log. Most existing automated process discovery techniques generate flat process models. When confronted to large event logs, these approaches lead to overly complex or inaccurate process models. An alternative is to apply a divide-and-conquer approach by decomposing the process into stages and discovering one model per stage. It turns out, however, that existing divide-and-conquer process discovery approaches often produce less accurate models than flat discovery techniques, when applied to real-life event logs. This article proposes an automated method to identify business process stages from an event log and an automated technique to discover process models based on a given stage-based process decomposition. An experimental evaluation shows that: (i) relative to existing automated process decomposition methods in the field of process mining, the proposed method leads to stage-based decompositions that are closer to decompositions derived by human experts; and (ii) the proposed stage-based process discovery technique outperforms existing flat and divide-and-conquer discovery techniques with respect to well-accepted measures of accuracy and achieves comparable results in terms of model complexity.     

基于环境影响的过程模拟分析

在工艺设计阶段避免和减少污染产生是从源头控制污染产生的有效方法,将环境影响最小集成到化工过程模拟设计中,是近年来清洁生产领域快速发展的一项技术。本文采用废物削减WAR算法来衡量工艺流程的环境影响指标,并将WAR算法与模拟软件Aspen集成,提供在工艺设计阶段的环境分析工具。同时,将集成的环境影响软件应用于乙烷制备乙烯工艺的环境影响分析。     

A semi-automated filtering technique for software process tailoring using neural network

It is widely known that implementation of the software development process to fit a given environment is the key to develop software at the lowest cost and highest quality. In general, applying an off-the-shelf software development process or an organizational process to a specific project can cause a lot of overhead if no effort is made to customize the given generic processes. Even though the process tailoring activities are done before starting a project, they are not given high importance. These activities depend on several process engineers who have a lot of experience and knowledge about process tailoring. Because of this dependence on human experience, it takes a long time to have a tailored process fit the project. To decide whether a specific task should be part of a given project or not is very time-consuming. Therefore, we suggest a semi-automated process tailoring method, which uses the artificial-neural network-based learning theory to reduce this time. We have demonstrated the effectiveness of our process filtering technique with a case study using process tailoring historical data as learning data.     

Modeling of process parameter selection with mathematical logic for process planning

Process planning is the systematic determination of detailed methods by which workpieces or parts can be manufactured economically and competitively from initial stages to finished stages. One of the key problems of computer-aided process planning (CAPP), however, is the complexity of process knowledge representation of process planning and the diversity of manufacturing background. Process knowledge representation and inference mechanism of process parameter selection is one of the most important issues in the research on CAPP. A proper methodology for modeling inference mechanism of process parameter selection, hence, is essential for selection of process parameters in process planning. The paper presents an atomic inference engine model of process parameter selection in process planning using mathematical logic. The methodology of modeling the inference mechanism of process parameter selection is proposed with backward chaining of mathematical logic that is a form of goal-directed reasoning. An illustrative case has been analyzed using the proposed approach to demonstrate its potential application in the real manufacturing environment, by combining with a practical application of a hole-making in a industrially relevant workpiece. The outcomes of this work provide a process reasoning mechanism for process parameter selection in process planning and thus alleviate automated process reasoning problems in process planning.     

软件过程建模语言研究

本文介绍了软件过程建模的基本概念，提出了对软件过程建模语言的基本要求并简要介绍了几个有代表性的过程建模语言，给出了一个基于时序逻辑的形式化过程建模语言ＸＹＺ／ＰＭＥ，该语言是时序逻辑语言ＸＹＺ／Ｅ的子语言，它支持以角色为中心的逐步求精的过程建模方法，可在统一的形式框架内表示不同抽象级的过程模型．软件过程，软件过程建模，过程建模语言，时序逻辑，程序设计语言．     

数据与知识驱动的零件特征工艺决策方法

在零件的工艺设计阶段, 加工工艺方案的生成强依赖于设计人员选择和应用的工艺知识. 而由于实际的生产环境与设计人员选择工艺知识存在着诸多偏差, 加工方案与实际的工艺过程不匹配成为当前零件制造领域关注的难题. 为解决上述问题, 本文提出了一种数据与知识双驱动的零件特征工艺决策方法. 本方法使用基于注意力机制的MLP深度学习算法, 从结构化工艺数据中挖掘工艺知识, 关联零件特征与特征工艺标签. 将其经过数据加工后, 用于训练神经网络模型. 经过验证, 该方法能够以零件特征的工艺数据为输入, 输出其对应的特征工艺标签的概率分布, 为零件工艺方案的选择提供决策支持.