Serial 3D model reconstruction for machining evolution of rotational parts by merging semantic and graphic process planning information

The manufacturing of a mechanical part is a dynamic evolution process from a raw workpiece to the final part, in which the generation of serial 3D models reflecting the changes on geometric shapes is especially critical to digital manufacturing. In this paper, an approach driven by the process planning course, the machining semantics and the machining geometry to reconstruct incrementally the serial 3D models for rotational part’s dynamic evolution is proposed. The two major techniques involved are: (1) extraction of machining semantics based on process planning language understanding; (2) 3D reconstruction from 2D procedure working drawings guided by machining semantics and visualization for the reconstructed series of 3D models. Compared with the conventional 3D reconstruction methods, this approach introduced the process planning course and relevant information to implement a dynamic, incremental and knowledge-based reconstruction which can greatly reduce the efforts in reconstruction and extend the collection of geometric shapes to be reconstructed.     

A case-based reasoning approach for automating disassembly process planning

One of the first processes for preparing a product for reuse, remanufacture or recycle is disassembly. Disassembly is the process of systematic removal of desirable constituents from the original assembly so that there is no impairment to any useful component. As the number of components in a product increases, the time required for disassembly, as well as the complexity of planning for disassembly rises. Thus, it is important to have the capability to generate disassembly process plans quickly in order to prevent interruptions in processing especially when multiple products are involved. Case-based reasoning (CBR) approach can provide such a capability. CBR allows a process planner to rapidly retrieve, reuse, revise, and retain solutions to past disassembly problems. Once a planning problem has been solved and stored in the case memory, a planner can retrieve and reuse the product's disassembly process plan at any time. The planner can also adapt an original plan for a new product, which does not have an existing plan in case memory. Following adaptation and application, a successful plan is retained in the case memory for future use. This paper presents the procedures to initialize a case memory for different product platforms, and to operate a CBR system, which can be used to plan disassembly processes. The procedures are illustrated using examples.     

The clustering-based case-based reasoning for imbalanced business failure prediction: a hybrid approach through integrating unsupervised process with supervised process

Case-based reasoning (CBR) is one of the main forecasting methods in business forecasting, which performs well in prediction and holds the ability of giving explanations for the results. In business failure prediction (BFP), the number of failed enterprises is relatively small, compared with the number of non-failed ones. However, the loss is huge when an enterprise fails. Therefore, it is necessary to develop methods (trained on imbalanced samples) which forecast well for this small proportion of failed enterprises and performs accurately on total accuracy meanwhile. Commonly used methods constructed on the assumption of balanced samples do not perform well in predicting minority samples on imbalanced samples consisting of the minority/failed enterprises and the majority/non-failed ones. This article develops a new method called clustering-based CBR (CBCBR), which integrates clustering analysis, an unsupervised process, with CBR, a supervised process, to enhance the efficiency of retrieving information from both minority and majority in CBR. In CBCBR, various case classes are firstly generated through hierarchical clustering inside stored experienced cases, and class centres are calculated out by integrating cases information in the same clustered class. When predicting the label of a target case, its nearest clustered case class is firstly retrieved by ranking similarities between the target case and each clustered case class centre. Then, nearest neighbours of the target case in the determined clustered case class are retrieved. Finally, labels of the nearest experienced cases are used in prediction. In the empirical experiment with two imbalanced samples from China, the performance of CBCBR was compared with the classical CBR, a support vector machine, a logistic regression and a multi-variant discriminate analysis. The results show that compared with the other four methods, CBCBR performed significantly better in terms of sensitivity for identifying the minority samples and generated high total accuracy meanwhile. The proposed approach makes CBR useful in imbalanced forecasting.     

A case-based expert support system for due-date assignment in a wafer fabrication factory

Owing to the complexity of wafer fabrication, the traditional human approach to assigning due-date is imprecise and very prone to failure, especially when the shop status is dynamically changing. Therefore, assigning a due date to each order becomes a challenge to the production planning and scheduling staff. Since most production orders are similar to those previously manufactured, the case based reasoning (CBR) approach provides a suitable means for solving the due-date assignment problem. This research proposes a CBR approach that employs the k-nearest neighbors concept with dynamic feature weights and non-linear similarity functions. The test results show that the proposed approach can more accurately predict order due dates than other approaches.     

Modelling for process planning: the links between process planning entities

In an integrated design framework, each actor of the design process must have his own view of the product to efficiently participate and co-design. The product model used by the process planner is presented here: it is in fact extracted from the global product model of the whole design system by filtering. The links of dependence among the different entities of the model – links of availability, accessibility and quality – are particularly emphasised in this text. Their efficiency has been tested in process planning and product designing.     

A time-varying geometry modeling method for parts with deformation during machining process

Deformation due to residual stress is a significant issue during the machining of thin-walled parts with low rigidity. If there are multiple processes with deformation during machining, some process suitability issues will appear. On this occasion, the actual geometric state of the deformed workpiece is needed for process adjustment. However, it is still a challenge to obtain the complete geometry information of deformed workpiece accurately and efficiently. In order to address this issue, a time-varying geometry modeling method, combining cutting simulation and in-process measurement, is proposed in this paper. The deformed workpiece model can be reconstructed via transforming the deformed workpiece with only a small amount of the measurement points by superimposing material removal and workpiece deformation simulation according to a time sequence, which takes advantage of the proposed Curved Surface Mapping based Geometric Representation Model (CSMGRM). Machining experiment of a typical structural part has shown that the deformed geometry model of the whole workpiece can be reconstructed within the error of 0.05mm, which is less than one tenth of the finish machining allowance in general cases, and it is sufficient to meet the accuracy requirements for interference or overcut/undercut analysis and process adjustment.     

A case-based reasoning approach to planning for disassembly

With recycling regulations, resource conservation needs and an increased awareness of the state of the environment by both the consumer and the producer, many companies are establishing disassembly plants and developing product designs that specifically facilitate disassembly. Once disassembled, the items can be reused, recycled or discarded. One can identify two distinct aspects of the disassembly problem: design for disassembly (DFD) and planning for disassembly (PFD). The goal of DFD is to design products that are easy to disassemble. On the other hand, the objective of PFD is to identify efficient sequences to disassemble products. This paper focuses on the PFD aspect of disassembly. Because there could be many ways to disassemble a given product, PFD knowledge is accumulated by experience. Such knowledge is valuable, and should be captured, saved and reused to solve similar problems that arise in the future. In this paper, we propose case-based reasoning (CBR) as an approach to solve PFD problems. CBR is based on the fundamental principle that problem solving can benefit from solutions to past problems that have been attempted. The technique and issues related to the application of CBR to PFD are presented.     

An overview of function block enabled adaptive process planning for machining

Small- and medium-sized enterprises (SMEs) in job-shop machining are experiencing more shop-floor uncertainties today than ever before, due to multi-tier outsourcing, customised product demands and shortened product lifecycle. In a fluctuating shop floor environment, a process plan generated in advance is often found unsuitable or unusable to the targeted resources, resulting both in wasted effort spent in early process planning and in productivity drop when idle machines have to wait for operations to be re-planned. Consequently, an adaptive process planning approach is in demand. Targeting shop-floor uncertainty, the objective of this research is to develop a novel adaptive process planning method that can generate process plans at runtime to unplanned changes. This paper, in particular, presents an overview of adaptive process planning research and a new methodology, including two-layer system architecture, generic supervisory planning, machine-specific operation planning, and adaptive setup planning. Particularly, function blocks are introduced as a core enabling technology to bridge the gap between computer systems and CNC systems for adaptive machining.     

Using case-based reasoning to establish a continuing care information system of discharge planning

As family structure changes, population is aging and disease styles tend to be chronic, long-term care in Taiwan becomes problematic, needs to be addressed, and requires immediate solution. Presently, many medical care institutions in the country have assisted patients in discharge planning; however, the lack of a standard evaluation procedure in the process of discharge planning is disturbing for each hospital. Without it, there might be huge differences in the evaluation results. Moreover, the lack of support and the uncertainty of case eligibility standard in these institutions further affect the performance of continuing care services.

This research adopted Case-Based Reasoning to establish a continuing care information system of discharge planning. With previously evaluated information of past cases, the similarity index is compared among new cases. In coordinate with Analytic Hierarchy Process, index weight is calculated to reason an old case that is most closely related to the condition of the new case. This information system can assist discharge-planning staff in accurately formulating a plan of action based on previous case-assessment experience and in obtaining valuable information that helps make decision. Through the implementation of the system, accumulation on knowledge and experience of continuing care models will help staff evaluate process of discharge planning to achieve a reasonable, standardized, and simplified procedure as a whole.

This research will transform the evaluating experience of discharge-planning professionals into an assessment method with the application of computer reasoning to make the evaluation process of discharge planning convenient as well as to save more time for discharge-planning professionals to further understand the actual conditions of each case. On the other hand, this information system will provide discharge-planning staff with a set of recommendations as references for making individual discharge plan. It is expected through this research that each hospital be provided with a blue print of improvement in case evaluation process and management.     

Knowledge-based treatment planning for adolescent early intervention of mental healthcare: a hybrid case-based reasoning approach

Abstract: Treatment planning is a crucial and complex task in the social services industry. There is an increasing need for knowledge-based systems for supporting caseworkers in the decision-making of treatment planning. This paper presents a hybrid case-based reasoning approach for building a knowledge-based treatment planning system for adolescent early intervention of mental healthcare. The hybrid case-based reasoning approach combines aspects of case-based reasoning, rule-based reasoning and fuzzy theory. The knowledge base of case-based reasoning is a case base of client records consisting of documented experience while that for rule-based reasoning is a set of IF–THEN rules based on the experience of social service professionals. Fuzzy theory is adopted to deal with the uncertain nature of treatment planning. A prototype system has been implemented in a social services company and its performance is evaluated by a group of caseworkers. The results indicate that hybrid case-based reasoning has an enhanced performance and the knowledge-based treatment planning system enables caseworkers to construct more efficient treatment planning in less cost and less time.     

Decision-based process planning for wire and arc additively manufactured and machined parts

The conventional manufacturing of aircraft components is based on the machining from bulk material and the buy-to-fly ratio is high. This, in combination with the often low machinability of the materials in use, leads to high manufacturing costs. To reduce the production costs for these components, a process chain was developed, which consists of an additive manufacturing process and a machining process. To fully utilize the process chain’s capabilities, an integrated process planning approach is necessary. As a result, the work sequence can be optimized to achieve the economically most suitable sequence. In this paper, a method for a joint manufacturing cost calculation and subsequent decision-based cost minimization is proposed for the wire and arc additive manufacturing (WAAM) & milling process chain. Furthermore, the parameters’ influence on the results and the magnitude of their influence are determined. These results make it possible to design an economically optimal work sequence and to automate the process planning for this process chain.     

CaBMA: a case-based reasoning system for capturing,refining, and reusing project plans

In this paper, we present CaBMA, a prototype of a knowledge-based system designed to assist with project planning tasks using case-based reasoning. CaBMA introduces a novel approach to project planning in that, for the first time, a knowledge layer is added on top of traditional project management software. Project management software provides editing and bookkeeping capabilities. CaBMA enhances these capabilities by automatically capturing project plans in the form of cases, refining these cases over time to avoid potential inconsistency between them, reusing these cases to generate plans for new projects, and indicating possible repairs for project plans when they derive away from existing knowledge. We will give an overview of the system, provide a detailed explanation on each component, and present an empirical study based on synthetic data.     

Case-based path planning for autonomous underwater vehicles

Case-based reasoning is reasoning based on specific instances of past experience. A new solution is generated by retrieving and adapting an old one which approximately matches the current situation. In this paper, we outline a case-based reasoning scheme for path planning in autonomous underwater vehicle (AUV) missions. An annotated map database is employed to model the navigational environment. Routes which are used in earlier missions are represented as objects in the map. When a new route is to be planned, the path planner retrieves a matching route from the database and modifies it to suit to the current situation. Whenever a matching route is not available, a new route is synthesized based on past cases that describe similar navigational environments. Case-based approach is thus used not only to adapt old routes but also to synthesize new ones. Since the proposed scheme is centered around reuse of old routes, it would be fast especially when long routes need to be generated. Moreover, better reliability of paths can be expected as they are adapted from earlier missions. The scheme is novel and appropriate for AUV mission scenarios. In this paper, we describe the representation of navigation environment including past routes and objects in the navigational space. Further, we discuss the retrieval and repair strategies and the scheme for synthesizing new routes. Sample results of both synthesis and reuse of routes and system performance analysis are also presented. One major advantage of this system is the facility to enrich the map database with new routes as they are generated.This work was supported in part by National Science Foundation Grant No. BCS-9017990.     

A case-based reasoning system development for statistical process control: Case representation and retrieval

Statistical process control (SPC) is a sub-area of statistical quality control. Considering the successful results of the SPC applications in various manufacturing and service industries, this field has attracted a large number of experts. Despite the development of knowledge in this field, it is hard to find a comprehensive perspective or model covering such a broad area and most studies related to SPC have focused only on a limited part of this knowledge area. According to many implemented cases in statistical process control, case-based reasoning (CBR) systems have been used in this study for developing of a knowledge-based system (KBS) for SPC to organize this knowledge area. Case representation and retrieval play an important role to implement a CBR system. Thus, a format for representing cases of SPC and the similarity measures for case retrieval are proposed in this paper.     

A case-based reasoning approach for building a decision model

A methodology based on case-based reasoning is proposed to build a topological-level influence diagram. It is then applied to a project proposal review process. The formulation of decision problems requires much time and effort, and the resulting model, such as an influence diagram, is applicable only to one specific problem. However, some prior knowledge from the experience in modeling influence diagrams can be utilized to resolve other similar decision problems. The basic idea of case-based reasoning is that humans reuse the problem-solving experience to solve new problems.
In this paper, we suggest case-based decision class analysis (CB-DCA), a methodology based on case-based reasoning, to build an influence diagram. CB-DCA is composed of a case retrieval procedure and an adaptation procedure. Two measures are suggested for the retrieval procedure, one a fitting ratio and the other a garbage ratio. The adaptation procedure is based on decision-analytic knowledge and decision participants' domain-specific knowledge. Our proposed methodology has been applied to an environmental review process in which decision-makers need decision models to decide whether a project proposal is accepted or not. Experimental results show that our methodology for decision class analysis provides decision-makers with robust knowledge-based support.     

A practical approach to a process planning expert system for manufacturing processes

In this paper the methodical techniques applied by the human process planning expertise is simulated. It considers the process plans design, or process selection. Software modules are designed to generate a process plan or several plans for a new part according to the input data from its engineering drawing. A specific module for each surface type, to match the surface parametric data and the required quantities with respect to the capability matrices, in order to locate the most eligible process plan is identified and used.     

e-CAPP: A distributed collaborative system for internet-based process planning

Advances in distributed technologies have enabled engineers to communicate more effectively, collaborate, obtain, and exchange a wide range of design resources during product development. Shared internet-based virtual environments allow experts in remote locations to analyze a virtual prototype, together and simultaneously in centers in which the product is being developed.This paper presents a system for distributed and collaborative environment which could assist manufacturing enterprises and experts in discussing, suggesting, evaluating and selecting best process plans for family of manufacturing parts. The represented e-CAPP system enables the implementation of expert knowledge in an appropriate knowledge repository. The knowledge from this repository is integrated into intra-company CAPP systems and used while generating process plans for new products. The proposed internet-based collaborative environment, dedicated to distributed process planning, is yet another step in the direction advancing of distributed manufacturing.     

A Web-based process planning optimization system for distributed design

In this paper, a process planning module, which can optimize the selection of machining resources, determination of set-up plans and sequencing of machining operations to achieve optimized process plans, has been wrapped as services and deployed in the Internet to support distributed design and manufacturing analysis. The module includes four intelligent approaches, and a Tabu search-based approach is explained in this paper to illustrate the optimization process. A Web-based prototype system has been setup for users to carry out visualization-based manipulations and process planning of design models by invoking the services remotely. The Web-based system has been integrated with a distributed feature-based design system, and the latter can generate design models and re-represent them in an XML representation based on VRML and attributes of features to provide the input of the former. Through effective utilization of the Web and Java technologies, this system is independent of the operating system, scalable and service-oriented, and can be used by a geographically distributed design team to organize concurrent engineering design activities effectively.     

Tennessee-Eastman过程的学习型案例推理故障诊断方法

为了提高Tennessee-Eastman(TE)过程的故障诊断准确率,本文研究一种学习型伪度量(learning pseudo metric,LPM)代替距离度量的案例检索方法,并建立了TE过程的案例推理(case-based reasoning,CBR)故障诊断模型.首先建立LPM度量准则并对LPM模型进行训练,其次度量目标案例与每一个源案例的相似度,从中检索与目标案例相似的同类案例,再采用多数重用原则从同类案例中决策出目标案例的解,最后通过TE过程的运行数据对该方法的性能进行测试,并与典型的CBR和BP(back-propagation)神经网络和支持向量机等方法进行对比,表明本文方法能有效提高故障诊断准确率,在实际化工过程中具有一定的推广应用价值.     

基于案例推理的层流冷却过程建模

针对具有非线性,参数时变,分布参数等综合复杂特性的热轧层流冷却过程,将机理建模方法与案例推理技术相结合,通过使用层流冷却过程中带钢的运行工况构造案例,在案例库中检索与其匹配的历史案例,利用实际工况的特征与匹配工况的特征经过推理给出当前工况的模型参数,从而确定层流冷却过程的动态模型.利用这一模型可以预测整个冷却过程中带钢的温度变化过程.通过某钢铁公司热轧层流冷却过程实际数据的实验比较表明所提出的建模方法是有效的.