Machining Process Planning Research Articles

Methodology for aluminium part machining quality improvement considering mechanical properties and process conditions

The manufacturing of structural aluminium alloy parts requires several steps of both forming processes and heat treatments. Before machining, which is usually the last step of the manufacturing, the workpiece has thus undergone multiple manufacturing steps involving unequal plastic deformations which are source of residual stresses. During machining, where up to 90% of the initial workpiece volume can be removed, the mechanical equilibrium of the part evolves constantly with the redistribution of the initial residual stresses. For thick, large and complex parts in highly alloyed aluminium, this redistribution of the residual stresses can leads to an unexpected behaviour of the workpiece and is the main reason for both workpiece deflections (during machining) and post-machining distortions (after unclamping). These two phenomena can lead to the nonconformity of the part with the geometrical and dimensional tolerance specifications and therefore to the rejection of the part or to additional conforming steps. As a consequence, the mechanical behaviour of the workpiece has to be considered during the definition of the machining process plan to improve the machining accuracy and the robustness of the process and thus to ensure the conformity of the machined part with the dimensional and geometrical specifications, i.e. to ensure the desired machining quality. In this paper, the numerical tool developed in [1] is used to conduct an analysis on the influence of the initial workpiece residual stress state, of the fixture layout as well as of the machining sequence on the machining quality. This analysis is performed on a part which has been specially designed and which can be considered as being representative of real aerospace parts. Several comparisons with experimental results are performed, one of them using digital image correlation (DIC) measurements. Results obtained show a good agreement, validating both the prediction of the behaviour of the workpiece during machining and the prediction of the machined part geometry. Based on the results of this analysis, a classification of the parameters has been performed depending on their influence on the machining quality. A first methodology allowing to define machining process plans adapted to the initial workpiece stress state has then been created based on the previous classification. This methodology is composed of a procedure and basic guidelines which are both presented in detail. An example of an application of this methodology is then introduced, demonstrating the benefits of the approach developed in this work.

An XML-based machining energy estimation tool from process plans

Excessive energy consumption has become a worldwide issue in today’s manufacturing industry. Software tools for estimating manufacturing energy consumption that could later be used to integrate with CAD/CAM systems are in demand. This research develops software tools for estimating manufacturing energy consumption in machining operations based on manufacturing process plans. This study first reviews literature and background in related areas and then presents the method to calculate manufacturing energy in machining operations. eXtended Markup Language (XML) has been adopted as the knowledge representation language for machining process plans and forms one of the inputs for energy estimation. Since XML plays an important role in estimating machining energy, this article introduces XML validation and parsing. The method is demonstrated via case studies for machining energy estimation in machining operations. The method will assist users who have little knowledge about energy computations to estimate energy consumption during the manufacturing phase. Such energy estimation can be used to redesign the part and assemblies, leading to products with reduced machining energy.

Prediction of machining quality due to the initial residual stress redistribution of aerospace structural parts made of low-density aluminium alloy rolled plates

During the machining of thick, large and complex aluminium parts, the redistribution of initial residual stresses is the main reason for machining errors such as dimensional variations and the post-machining distortions. These errors can lead to the rejection of the parts or to additional conforming operations increasing production costs. It is therefore a requirement to predict potential geometrical and dimensional errors resulting from a given machining process plan and in taking into consideration the redistribution of the residual stresses. A specific finite element tool which allows to predict the behaviour of the workpiece during machining due to its changing geometry and to fixture-workpiece contacts has been developed. This numerical tool uses a material removal approach which enables to simulate the machining of parts with complex geometries. In order to deal with industrial problems this numerical tool has been developed for parallel computing, allowing the study of parts with large dimensions. In this paper, the approach developed to predict the machining quality is presented. First, the layer removal method used to determine the initial residual stress profiles of an AIRWAREⓇ 2050-T84 alloy rolled plate is introduced. Experimental results obtained are analysed and the same layer removal method is simulated to validate the residual stress profiles and to test the accuracy of the developed numerical tool. The machining of a part taken from this rolled plate is then performed (experimentally and numerically). The machining quality obtained is compared, showing a good agreement, thus validating the numerical tool and the developed approach. This study also demonstrates the importance of taking into account the mechanical behaviour of the workpiece due to the redistribution of the initial residual stresses during machining when defining a machining process plan.

Influence of the machining sequence on the residual stress redistribution and machining quality: analysis and improvement using numerical simulations

The manufacturing of aluminium alloy structural aerospace parts involves multiple steps, the principal ones being the forming (rolling, forging etc.), the heat treatments and the machining. During this last step, the final geometry of the part is obtained. Before machining, the workpiece has therefore undergone several manufacturing steps resulting in unequal plastic deformation and metallurgical changes which are both sources of residual stresses. On large and complex aluminium alloy aeronautical parts, up to 90 % of the initial workpiece volume can be removed by machining. During machining, the mechanical equilibrium of the part is in constant evolution due to the redistribution of the initial residual stresses.The residual stress redistribution is the main cause of workpiece deflections during machining as well as of post-machining distortion (after unclamping). Both can lead to the non-conformity of the part with the geometrical and dimensional tolerance specifications and therefore to a rejection of the part or to additional conforming steps. In order to improve the machining accuracy and the robustness of the process, the effect of the residual stresses has to be considered for the definition of the machining process plan. In this paper, a specific numerical tool [2] allowing to predict workpiece deflections during machining and post-machining distortion is used to study the influence of the machining sequence on the machining quality in taking into consideration the initial residual stresses. A first machining process plan defined as the reference case is simulated. Simulation results are then compared with experimental ones showing the feasibility to use the developed tool to predict the machining quality depending on the initial residual stresses, the fixture layout and the machining sequence. Using the computational tool, a method to optimise the machining quality depending on the initial workpiece and on the machining sequence is presented. A machining process plan allowing to respect the tolerance specifications is then defined. This demonstrates the feasibility to adapt and to optimise the machining process plan to ensure conformity of the part with the tolerance specifications.

A Framework for Explicating Formal Geometrical and Dimensional Tolerances Schema From Manufacturing Process Plans for Three-Dimensional Conformance Analysis

A process plan is an instruction set for the manufacture of parts generated from detailed design drawings or computer-aided design (CAD) models. While these plans are highly detailed about machines, tools, fixtures, and operation parameters, tolerances typically show up in less formal manner, if at all. It is not uncommon to see only dimensional plus/minus values on rough sketches accompanying the instructions. On the other hand, design drawings use standard geometrical and dimensional tolerances (GD&T) symbols with datums and datum reference frames (DRFs) clearly specified. This is not to say that process planners do not consider tolerances; they are implied by way of choices of fixtures, tools, machines, and operations. Process planners do tolerance charting in converting design tolerances to the manufacturing datum flow based on operation sequence, but the resulting plans cannot be audited for conformance to design specification. In this paper, we present a framework for explicating the GD&T schema implied by machining process plans. The first step is to derive DRFs from the fixturing method in each setup. Then, basic dimensions for features machined in the setup are determined with respect to the extracted DRF. Using shop data for the machines and operations involved, the range of possible geometric variations are estimated for each type (form, size, orientation, and position). The sequence of operations determines the datum flow chain. Once we have a formal manufacturing GD&T schema, we can analyze and compare it to design specification using the T-map math model.

An approach to mapping machining feature to manufacturing feature volume based on geometric reasoning for process planning

Efficient construction in three-dimensional working procedure model has an important effect on the efficiency and quality of machining process planning. This article proposes an algorithm to mapping machining features to manufacturing feature volumes from B-rep of mechanical part, and then, the working procedure models are generated. The mapping strategy is performed in three steps. In the first step, three types of machining features, such as depression feature, protrusion feature and transition feature, are introduced. In the second step, the edges of the chosen seed face and its neighboring faces are searched in order to generate the machining feature faces. The last step applies a closure to the machining feature faces to generate a compact solid by applying additional neighboring faces and their extensions. Then, the working procedure models are formed by combining the mapped manufacturing feature volumes with the final parts model. Compared with the existing working procedure model’s generation methods, this approach can avoid the unnecessary conversions from the engineering drawing to three-dimensional process models and from the machining knowledge to the modeling knowledge, which can greatly reduce the planning time on modeling. To validate the feasibility and validity of this approach, two machined parts with complex machining features are tested in the developed prototype computer-aided process planning system.

Development of a CAD-CAM Interaction System to Generate a Flexible Machining Process Plan

A unique machining knowledge has led to several different perspectives between planners and operators as regards in designing a machining process plan. All precedents have shown the need to maintain a suitable machining process plan. Commercial Computer-Aided Design (CAD) and Computer-Aided Manufacturing (CAM) systems have facilitated the manipulation of 3D models to generate a machining process plan. The open Advanced Programming Interfaces (APIs) are also helpful in tailoring decision support systems to determine process plans. This study proposes an emergent system to generate flexible machining process plans. The proposed system considers the integration between design and manufacturing perspective to produce relevant machining process plan. The generation of process plans begins by considering the total removal volume of the raw material, estimating the removal features, thus analyzing and ordering several candidates of machining process plans. The total machining time and number of setups from each machining process plan candidate is analyzed and evaluated. Eventually, the proposed system is tested using several prismatic 3D models of a workpiece to show the outcomes.

Research on the knowledge recognition and modeling of machining feature geometric evolution

To discover the knowledge from the machining process planning, it is important to obtain the geometric change of machining feature firstly. This paper proposed a methodology to acquire and describe the change process of machining feature. First, the concept of global machining datum is presented to construct the attributed adjacency graph for faces on the process model. The datum attribute of the vertex correspondent to the face is the unique identifier of correspondent face in the process model sequence. The datum attribute of the vertex, corresponding to the model face, is used to discern the correspondent faces in adjacent process model sequence. Second, the new faces, extinct faces, and maintained faces in adjacent procedure are classified by detecting the parameter changes. Third, with the help of the change types and interrelation of the faces, an algorithm is presented for geometric changes recognition of machining feature. As a result, the change process of a machining feature is discerned as a sequence of machining status. At last, the evolution of machining feature recognition method is verified with an example of machining process planning.

An ontology for integrated machining and inspection process planning focusing on resource capabilities

The search for and assignment of resources is extremely important for the efficient planning of any process in a distributed environment, such as the collaborative product integrated development process. These environments require a degree of semantic interoperability, which currently can only be provided by ontological models. However, the ontological proposals centred on Resources for Machining and Inspection Process Planning have a limited reach, do not adopt a unified view of machining and inspection, and fail to express knowledge in the manner required by some of the planning tasks, as is the case with those concerned with resource assignment and plan validation. With the aim of providing a solution to these shortcomings the manufacturing and inspection resource capability (MIRC) ontology has been developed, as a specialist offshoot of the product and processes development resources capability ontology. This ontology considers resource capabilities to be a characteristic of the resource executing any activity present in an integrated process plan. Special attention is given to resource preparation activities, due to their influence on the quality of the final product. After describing the MIRC ontology, a case study demonstrates how the ontology supports the process planning for any level, approach or plan strategy.

Ontological-based Validation of Selected Technological Resources in Integrated Machining and Inspection Process Planning

Based on previous research carried out to characterise the capacities of the resources involved in the execution of process planning, in this paper a methodology is presented for validating the configurations of resources assigned to the activities of integrated machining and inspection process planning. The methodology utilises concepts from the MIRC ontology and has graphic support that makes it more user-friendly. It also places special emphasis on the preparation activities used in the configurations of the resources and has been conceived as an aid to help in the final steps of the development of the process plan.

Manufacturing of Custom-made Parts for Assembly of Large Aircraft Components

The manufacturing of custom-made parts requires the development of strategies integrating design and manufacturing. The need for custom-made parts is increasing constantly due to its application in different industrial sectors: medical prosthesis, car parts, aircraft parts, etc. Under such context, this paper describes a part of the MISTRAL (Methods of InverSe engineering To develop RApid prototyping tooLs) project. Taking a file with clouds of points as main input, the aim was to generate CAD models and machining process plans for custom-made parts. The parts are different for every aircraft produced, since they have to fit in with large components, whose real geometry is subject to variable deformation states in the assembly process. This paper presents a prototype development carried out mainly in CATIA v5. The developed solution was tested with a typical family of parts.

1906 Generative Machining Process Planning System Based on Total Removal Volume Concept

1906 Generative Machining Process Planning System Based on Total Removal Volume Concept

Computer–aided planning of machining processes

Process planning is the intermediate stage between product design and manufacture, where the geometrical design data is used for the determination of the technical manufacturing data. While considerable attention has been paid to the development of CAD/CAM systems, the process planning activity, which is an important link between design and manufacturing, has had only limited interest. In spite of the extensive investigations carried out in the field of automated process planning, there still seems to be no reliable integrated system which covers the different manufacturing processes. Some of the available systems are applicable only to a few parts produced by a particular process or on a particular type of machine, while others are applicable only to a small variety of parts. In the present paper, an automated process planning system is developed which can be applied to different manufacturing processes and workpiece shapes.

3D Machining Process Planning Based on Machining Feature Recognition Technique

In the model-based definition (MBD) scheme, activities of process planning need to be carried out in 3D environment. To realize the 3D computer-aided process planning (3D CAPP), the design solid model needs to be transferred into a representation as manufacturing features, features’ process requirement and product manufacturing information (PMI), and then the generative process planning techniques can be realized by inferring machining operations based machining feature knowledge base. A machining feature-based 3D computer-aided process planning approach is proposed for machining part. Design model is transferred into boundary representation (B-Rep). According to a machining features classification scheme, hybrid machining feature recognition technique is introduced. A part process information model is generated including machining features, feature relationship, feature’s process chain. For each recognized machining feature, a feature’s process chain is inferred from feature knowledge base, based on feature type, process requirements, dimension and tolerances, and the enterprise manufacturing resources. Process intermediate models corresponding to each process operation are generated automatically by applying geometry local modification operations. The complete process plan is generated and documented with detailed operation information and 3D process intermediate models. A 3D CAPP tool is developed on ACIS/HOOPS, with industrial cases to demonstrate the feasibility and applicability of proposed method.

Workpiece Setup Simulation based on Machinable Space of Five-axis Machining Centers

An actual machining center specification, e.g. the axes travel, the workpiece size allowance, etc., needs to be considered for constructing a machining process plan. In this paper, a machinable space of a five-axis machining center is proposed for simulating the workpiece setup. The machinable space is constructed by a table region and a tool cone. The tool cone is an allowance of the spindle diameter and the cutting tool length. By fitting in the visibility area from a total removal volume (TRV) of the machining process plan, a TRV network can be established. The workpiece setup is estimated by positioning the TRV network within the table region. The positioning process can be used for estimating the number of setup changes on the corresponding machinable space.

Process Planning for CNC Machining of Swedish Subcontractors – A Web Survey

Process planning of CNC machining is critical to ensure cost, time and quality parameters of manufacturing operations. At the heart of process planning is, typically the process planner, who must make a multitude of decisions regarding machines, cutting strategies, tools and process parameters etc. Today there are a number of different tools and methods available to aid the process planner. This paper explores today's industrial use of some of these aids and outlines potential underlying reasons for the current state. The empirical data is based on a questionnaire survey of Swedish CNC machining sub-contractors. The main conclusion is that despite a long history of development of various aids (CAD/CAM, PLM standards etc.) there is still a large proportion of the industry, which has not yet adopted these aids. By the responding companies 32% do not use any CAM system and only 2% use a PLM system. On the other side of the spectrum is a group of 25% that uses CAM in 75% or more of their planned products. The learning from this survey can be used to better understand the industrial needs and focus research and development efforts.

Tolerance chart-based methodology for integrated CNC machining and in-line inspection planning

In this work, a methodology based on a new and extended use of tolerance charting, that allows incorporation of in-line inspection operations to improve the machining process plan, is presented. The methodology is applied to every process plan setup, from the last to the initial one, and is based on a unified approach for the different active part features (machining features, inspection features and setup datum features) in the setup. A direct transfer of the inter-setup specifications to working and offset specifications tolerances is proposed. In this way, the variability sources originated by setting and tool deviations can be separately considered. This circumstance allows a more accurate calculation of operation capability indexes and eases the analysis and improvement of critical operations, reducing the manufacturing and quality loss costs. To prove methodology potential, an application on a part process planning on a CNC machine with on-machine measurement capability is illustrated.

Study of machining parameters optimization for different materials in WEDM

In process planning of wire electrical discharge machining (WEDM), determination of appropriate machining conditions is likely to face problems in many ways. In addition to the construction of the relationship between machining parameters and machining characteristics, optimization search technique, a large number of experiments must be conducted repeatedly to renew parameters for different workpiece materials. The concept of specific discharge energy (SDE) was employed in this paper to represent the WEDM property of workpiece materials as one of the machining parameters. Two kinds of materials with distinctive SDE values, i.e., higher and lower, respectively, were selected for our experiments. The experimental data obtained were used, and a neural network that can accurately predict the relationship between machining parameters and machining characteristics was constructed. It was found that the predicted error was less than 7 %. The optimization technique of genetic algorithms was employed, and the optimal combination of machining parameters that meet the required machining characteristics for different workpiece materials was obtained. The system proposed in this study is both user-friendly and practical. It can save considerable time and cost during the construction of the database for the expert system of process planning.

Optimizing Maintenance Strategy of Multi-Stage Production System Based on Genetic Algorithm and Configuration

The optimized maintenance strategy of multi-stage production line is influenced by device processing ways, parts process plan and equipment deterioration process and other factors. Moreover, the production processes of parts exist constraint relationship. Based machining process plan of complex parts, the order relations of its operation processes is analyzed; the optimized multi-stage production line maintenance model is constructed with multiple objectives including production time, maintenance time, production cost and maintenance cost; the genetic algorithm is used to solve the model, and the Monte Carlo method is applied to carry out the simulation computation for fitness function of chromosome of genetic algorithm; the results give the maintenance threshold of each equipment of the line, their configurations and allocation of the various operation processes of parts at the same time. Finally, an example is presented to prove the effectiveness.

Research on Green Manufacturing-Oriented Machining Process Planning

This paper studies the connotation and features of green manufacturing-oriented machining process planning and the methods to optimize it. It argues that, through optimized decision making and planning concerning process routes, process methods, process equipments, process parameters, process programs and so forth, each phase of the technological procedure can be improved to be more environmental friendly. Hence both economic and social benefits will be coordinated and optimized during product production. Fewer resources will be consumed and the negative influence on the environment will be mitigated.