Manufacturing Process Planning Research Articles

VCS: value chains simulator, a tool for value analysis of manufacturing enterprise processes (a value-based decision support tool)

Manufacturing enterprises are facing a competitive challenge. This paper proposes the use of a value chain based approach to support the modelling and simulation of manufacturing enterprise processes. The aim is to help experts to make relevant decisions on product design and/or product manufacturing process planning. This decision tool is based on the value chain modelling, by considering the product requirements. In order to evaluate several performance indicators, a simulation of various potential value chains adapted to market demand was conducted through a Value Chains Simulator (VCS). A discrete event simulator is used to perform the simulation of these scenarios and to evaluate the value as a global performance criterion (balancing cost, quality, delivery time, services, etc.). An Analytical Hierarchy Process module supports the analysis process. The value chain model is based on activities and uses the concepts of resource consumption, while integrating the benefiting entities view point. A case study in the microelectronic field is carried out to corroborate the validity of the proposed VCS.

Optimization of Machining Process for Aluminum Alloy Thin-Walled Supporting Part on UG NX

According to the structural features of the supporting part, the manufacturing process plan of it is made and the fixtures are designed. The process parameters are optimized by the means of setting up multi-objective function that cover productivity, cost of production, processing efficiency; The NC Programs of supporting part are drawn with UG CAM and the machining tool-path is optimized through machining simulation.

Automated plan assessment in cognitive manufacturing

In a cognitive factory setting, product manufacturing is automatically planned and scheduled, exploiting a knowledge base that describes component capabilities and behaviors of the factory. However, because planning and scheduling are computationally hard, they must typically be done offline using a simplified system model, and are thus unaware of online observations and potential component faults. This leads to a problem: given behavior models and online observations of possibly faulty behavior, how likely is each manufacturing process plan to still succeed? In this work, we first formalize this problem in the context of probabilistic reasoning as plan assessment. Then we contribute a solution which computes plan success probabilities based on most likely system behaviors retrieved from solving a constraint optimization problem. The constraint optimization problem is solved using well-optimized off-the-shelf solvers. Results obtained with a prototype show that our method can guide systems away from plans which rely on suspect components.

Automated setup and fixture planning system for box-shaped parts

The topic of the research is related to the domain of computer-aided manufacturing process planning. This paper deals with the problem of setup and fixture planning for the machining of box-shaped parts on the horizontal machining centres. The setup and fixture planning involves the definition of setups, the setup sequence and conceptual design of fixtures for each setup. The central topic of this research is the automation of the conceptual design of fixtures. This topic is interconnected with the setup planning, and accordingly, the aim of the author has been the integrated handling of tasks of setup and fixture planning and the finding of solution in an integrated system. Based on the workpiece model, the developed system automatically determines the setup sequence, the content of setups and the conceptual solution of fixture for each setup. The paper presents the problems of fixture solutions and the partial tasks of workpiece holding, the typical solution of partial tasks and the conditions of their application and finally offers a new method, which makes the integrated handling of tasks of setup and fixture planning and finding solution in an integrated system possible.

A contemporary study into the application of neural network techniques employed to automate CAD/CAM integration for die manufacture

In recent years, collaborative research between academia and industry has intensified in finding a successful approach to take the information from a computer generated drawings of products such as casting dies, and produce optimal manufacturing process plans. Core to this process is feature recognition. Artificial neural networks have a proven track record in pattern recognition and there ability to learn seems to offer an approach to aid both feature recognition and process planning tasks. This paper presents an up-to-date critical study of the implementation of artificial neural networks (ANN) applied to feature recognition and computer aided process planning. In providing this comprehensive survey, the authors consider the factors which define the function of a neural network specifically: the net topology, the input node characteristic, the learning rules and the output node characteristics. In additions the authors have considered ANN hybrid approaches to computer aided process planning, where the specific capabilities of ANN’s have been used to enhance the employed approaches.

Process planning strategies for solid freeform fabrication of metal parts

Process planning of additive manufacturing of metals is a research interest because of the applications of solid freeform fabrication of metal parts in industry. The strategy is to transform the model of the part into the combinations of 2D layers that will be deposited using different fabrication methods. Process planning for metal deposition in this paper consists of three major modules: spatial decomposition, slicing of the part, and toolpath generation for every slicing layer. Algorithmic improvements are proposed and implemented for these major modules. For spatial decomposition, 3D part decomposition based on modular boundary models and centroidal axis extraction methods are combined to decompose parts more robustly and reliably. For generating slicing layers, a planning process for building non-uniform layers is investigated to greatly increase the variety of the parts that can be manufactured without the need of support structure. For toolpath generation methods, optimization of the generated toolpath is studied especially for complex thin-wall structures to ensure the deposition quality. Experiments were carried out to evaluate the improvements of the major modules of process planning strategies for rapid manufacturing.

Applications of Software Engineering to Manufacturing Process Planning

Agile methods of software development promote the use of flexible architectures that can be rapidly refactored and rebuilt as necessary for the project. In the mechanical engineering domain, software tends to be very complex and requires the integration of several modules that result from the efforts of large numbers of programmers over several years. Such software needs to be extensible, modular, and adaptable so that a variety of algorithms can be quickly tested and deployed. This paper presents an application of the unified process (UP) to the development of a research process planning system called CyberCut. UP is used to (1) analyze and critique early versions of CyberCut and (2) to guide current and future developments of the CyberCut system. CyberCut is an integrated process planning system that converts user designs to instructions for a computer numerical control (CNC) milling machine. The conversion process involves algorithms to perform tasks such as feature extraction, fixture planning, tool selection, and tool-path planning. The UP-driven approach to the development of CyberCut involves two phases. The inception phase outlines a clear but incomplete description of the user needs. The elaboration phase involves iterative design, development, and testing using short cycles. The software makes substantial use of design patterns to promote clean and well-defined separation between and within components to enable independent development and testing. The overall development of the software tool took about two months with five programmers. It was later possible to easily integrate or substitute new algorithms into the system so that programming resources were more productively used to develop new algorithms. The experience with UP shows that methodologies such as UP are important for engineering software development where research goals, technology, algorithms, and implementations show dramatic and frequent changes.

Information modeling for variation management during the product and manufacturing process design

For car and aircraft industries, Design for Manufacturing, Robust Design and Conceptual Process Planning are a key activity to evaluate manufacturability, to improve design in the product development stage. Moreover, the inherent imperfections of manufacturing processes and resources (Manufacturing Process Key Characteristics, MPKCs) involve a degradation of functional part or product characteristics (Part / Product Key Characteristics, PKCs). The management of Key Characteristics (KCs) has become an important issue in product and process design and concurrent engineering. In order to ensure a certain level of quality, to assess the manufacturability, to select resources and to improve design, it is important to know the causality between MPKCs and PKCs. Effective reuse of enterprise knowledge about causality is a key strategic component of integrated product and processes development. The goal here is to put the management of KCs in a concurrent engineering context. There is an important question that would need to be looked upon: How to formalize and to capitalize the causality between MPKCs and PKCs? Therefore, to formalize and to capitalize this causality, we describe an information model.

Metallurgical and mechanical analysis from thixoforging steel shape

Since always, Industry minimizes manufacturing process plan and increases mechanical behaviour. In this topic, the thixoforging process offers important perspectives especially steel thixoforging. It is on the way of industrial development between casting and forging process.Previous works have illustrated the importance many parameters such as steel grade, slide speed, slug and tool temperature on the geometry from thixoforging part and of the forming load.This paper completes the previous results. It presents an analysis from mechanical resistance of samples extracted of from thixo-extrusion parts on a high speed hydraulic press. This strength investigation is correlated with metallurgical analysis. Macrograph analyses allow identifying the material yield during the process and the different phases.

Combining an ontology representation with rule-based reasoning for the process planning of bulk silicon micro-manufacturing

Based on feature modelling technology, a method to automatically generate the manufacturing process plan from a 3D model of micro-device is presented to support the top-down design flow. First, by the fabrication-oriented features mapping technology, the process model is constructed to benefit the follow-up reasoning procedure. Second, in accordance with the ontological representing mode, the knowledge in bulk silicon micro-manufacturing is hierarchically organised to make a basis for the definition of the reasoning rules, construction of the knowledge templates and generation of the initial facts. Finally, the micro-manufacturing process planning result is obtained through the rule-based reasoning approach.

Clustering techniques and their applications in engineering

Clustering is an important data exploration technique with many applications in different areas of engineering, including engineering design, manufacturing system design, quality assurance, production planning and process planning, modelling, monitoring, and control. The clustering problem has been addressed by researchers from many disciplines. However, efforts to perform effective and efficient clustering on large data sets only started in recent years with the emergence of data mining. The current paper presents an overview of clustering algorithms from a data mining perspective. Attention is paid to techniques of scaling up these algorithms to handle large data sets. The paper also describes a number of engineering applications to illustrate the potential of clustering algorithms as a tool for handling complex real-world problems.

MRP (Decision Support System For Manufacturing Process Planning And Controlling by Using )OLAP( Technique

MRP (Decision Support System For Manufacturing Process Planning And Controlling by Using )OLAP( Technique

Collaborative design and manufacturing process planning in tooling industry

Manufacturing process planning plays a significant role by providing collaborative integration capabilities, from design to manufacturing. This situation is more acute in the tooling production industry, which is characterised by short lead-time and frequent dynamic customer requirements. A framework for collaborative integration between computerised design and manufacturing has been developed to support the integration of product design with manufacturing process planning. A prototype system based on this framework has been developed and tested in a tooling job shop with satisfactory results. The integration framework is also expected to be effectively applied in other similar enterprise application domains.

Development of an ERP Model for Modularly Designed Ships for Medium Scale Shipyards – I: Manufacturing Management

Enterprise Resource Planning (ERP) has become something of a magic wand for largemanufacturing industries because of its capability to integrate different manufacturingmodules via online networks and hence providing one window access thereby makingthe whole manufacturing process integrated with a reduction in inventory. Ship productionis not a manufacturing process in a strict sense because of high customisation,widely varying scales of operations and less compatibility between various productionprocesses. Ship production is planned in an activity driven network scheduling system ingeneraland is assumed more as a construction process or assembling process ratherthan a manufacturing process. An ERP principle is based upon information managementand process integration and hence is effective in all manufacturing processes that needto integrate the processes for streamlined, lean and synergised manufacturing. A modularapproach to design has been regarded as the new logic for product design and itsorganisation, as it helps design and manufacturing firms to cope with the present volatileand turbulent environment. This combines the ERP principle and modular approach todesign. The ERP principle is used to design the manufacturing management system forthe modularly designed ships. In this series of two papers, we discuss development of anERP model for a medium scale shipyard. Part I, discusses a methodology for manufacturingmanagement: planning and integration of ship manufacturing processes for themodularly designed ships in a medium size shipyard. The manufacturing management isintegration driven and is based upon activity based network scheduling. In this work, it isshown that by combining network scheduling, ERP and modular approach to design, theship manufacturing process will be more streamlined, better planned and executed.

A B-spline-based approach to heterogeneous objects design and analysis

The recent advancement of solid freeform fabrication, design techniques and fundamental understanding of material properties in functionally graded materials has made it possible to design and fabricate multifunctional heterogeneous objects. In this paper, we present an integrated design and analysis approach for heterogeneous object realization, which employs a unified design and analysis model based on B-spline representation and allows for direct interaction between the design and analysis model without laborious meshing operation. In the design module, a new approach for intuitively modelling of multi-material objects, termed heterogeneous lofting, is presented. In the analysis module, a novel graded B-spline finite element solution procedure is described, which gives orders of magnitude of better convergence rate in comparison with current methods, as demonstrated in several case studies. Further advantages of this approach include simplified mesh construction, exact geometry/material composition representation and easy extraction of an isomaterial surface for manufacturing process planning.

Fabrication of lightweight structural panels through ultrasonic consolidation

A fundamental investigation of the feasibility of producing lightweight structural panels using ultrasonic consolidation (UC) was undertaken. As a novel solid freeform fabrication technology, UC utilizes both additive ultrasonic joining and subtractive CNC milling to enable the creation of complex aluminum structures with internal geometry at or near room temperature. A series of experiments were performed to understand the issues associated with sandwich structure fabrication using UC, including peel test experiments which evaluated the bond strength for various geometric configurations. The honeycomb lattice was found to offer the best core configuration due to its ability to resist vibration from the sonotrode and provide adequate support for pressure induced by the sonotrode. UC was found to be capable of producing lightweight and stiff structures, including honeycomb and other sandwich panels, without the use of adhesives. An effective manufacturing process plan for fabricating structural panels was developed. A case study was performed on a deck built for the TOROID small satellite spacecraft. The fabricated deck was tested for mechanical integrity. Finally, the cost and benefits of utilizing UC for lightweight structural panels versus traditional fabrication methods are discussed.

Applications of agent-based systems in intelligent manufacturing: An updated review

Agent technology has been recognized as a promising paradigm for next generation manufacturing systems. Researchers have attempted to apply agent technology to manufacturing enterprise integration, enterprise collaboration (including supply chain management and virtual enterprises), manufacturing process planning and scheduling, shop floor control, and to holonic manufacturing as an implementation methodology. This paper provides an update review on the recent achievements in these areas, and discusses some key issues in implementing agent-based manufacturing systems such as agent encapsulation, agent organization, agent coordination and negotiation, system dynamics, learning, optimization, security and privacy, tools and standards.

Application of mobile agents in interoperable STEP-NC compliant manufacturing

As the ratio of transport costs to total product cost increases, manufacturers try to fulfil the demands of each geographical region with products manufactured within the same region. Since the manufacturing resources available at each venue can be varied, it is necessary to adapt the manufacturing process plan for each production facility. Traditionally, this process is carried out manually by engineers utilizing computer-aided design (CAD) files. With the advances in artificial intelligence technology and emergence of integration standards such as STEP, it is now possible to automate the CAD/computer-aided manufacturing (CAM)/computer numerical control (CNC) interface. Distributed artificial intelligence techniques and mobile agents in particular can be used to transfer information throughout the manufacturing network and construct the distributed knowledge-base required for the intelligent interoperable integration of product data models and manufacturing resources. This paper explores the application of mobile agents as enablers of interoperability in a global manufacturing enterprise. A novel manufacturing chain based on the STEP-NC standard is proposed and the application of agents for transfer of manufacturing information is studied. The research is demonstrated through the use of a prototype manufacturing decision support system developed using agents.

Boundary analysis and geometric completion for recognition of interacting machining features

Features are the basic elements which transform CAD data into instructions necessary for automatic generation of manufacturing process plans. In this paper, a hybrid of graph-based and hint-based techniques is proposed to automatically extract interacting features from solid models. The graph-based hints generated by this approach are in geometrical and topological compliance with their corresponding features. They indicate whether the feature is 2.5D, floorless or 3D. To reduce the product model complexity while extracting features, a method to remove fillets existing in the boundary of a 2.5D feature is also proposed. Finally, three geometric completion algorithms, namely, Base-Completion, Profile-Completion and 3D-volume generation algorithms are proposed to generate feature volumes. The base-completion and profile-completion algorithms generate maximal volumes for 2.5D features. The 3D volume generation algorithm extracts 3D portions of the part.

Selection and validation of predictive regression and neural network models based on designed experiments

Model selection and validation are critical in predicting the performance of manufacturing processes. The correct selection of variables minimizes the model mismatch error whereas the selection of suitable models reduces the model estimation error. Models are validated to minimize the model prediction error. In this paper, the relevant literature is reviewed and a procedure is proposed for the selection and cross-validation of predictive regression analysis and neural network models. Specifications on surface roughness and tolerances impact on manufacturing process plans, and differentiate product quality, and ultimately the product cost and lead times. Experimental data from a turning surface roughness study is used to demonstrate the developed concepts with regression and neural network techniques being used for the purpose of predictive rather than descriptive modeling.