Manufacturing Process Planning Research Articles

Unbounded Orchestrations of Transducers for Manufacturing

There has recently been increasing interest in using reactive synthesis techniques to automate the production of manufacturing process plans. Previous work has assumed that the set of manufacturing resources is known and fixed in advance. In this paper, we consider the more general problem of whether a controller can be synthesized given sufficient resources. In the unbounded setting, only the types of available manufacturing resources are given, and we want to know whether it is possible to manufacture a product using only resources of those type(s), and, if so, how many resources of each type are needed. We model manufacturing processes and facilities as transducers (automata with output), and show that the unbounded orchestration problem is decidable and the (Pareto) optimal set of resources necessary to manufacture a product is computable for uni-transducers. However, for multitransducers, the problem is undecidable.

Time Optimization Analysis Using Hybrid Simulated Annealing and Genetics Algorithm For CNC Punching Machine

This research describes the method of manufacturing process planning of hole manufacturing, which in every machining process consists of several individual operations with various types of punching blades. The process of setting the trajectory is one of the problems of holes manufacturing process because this process takes a long machining time and often it obtains undirected sequence path that sometimes causes stress material and the damaged of punching blades. The aim of optimization process is to minimize the processing time of holes manufacturing so the time function which is obtained can be converted in the form of energy consumption that helps manufacturers to predict the machining time. Dynamic Directed Graph is applied where each node represents a machining operation. The time function is obtained by studying the shortest path of a directed graph where the structure of objectivity studied is similar to the Traveling Salesman Problem (TSP). The mathematical model is used to solve the hole optimization problem of the graph structure by proposing the combination of both to solve the optimization problem. The Algorithm realization will be applied in real time CAD / CAM programming by using TOPS300 which is used for TRUMPF TC200 Punching Machine. There are 2 kinds of blade operations in this research which are single stroke operation and multi strokes operation. Both produce different time function. By a. Finally, some conclusions are given from examples that show the hybrid algorithm of Simulated Annealing and Genetic Algorithms is effective in reaching higher optimization performance and less energy consumption, which 26.02 seconds for single stroke operation and 126.02 seconds for multi strokes operation with the acquisition of logical path results with the absence of intersecting trajectories.

On-line part deformation prediction based on deep learning

Deformation prediction is the basis of deformation control in manufacturing process planning. This paper presents an on-line part deformation prediction method using a deep learning model during numerical control machining process, which is different from traditional methods based on finite element simulation of stress release prior to the actual machining process. A fourth-order tensor model is proposed to represent the continuous part geometric information, process information, and monitoring information, which is used as the input to the deep learning model. A deep learning framework with a conventional neural network and a recurrent neural network has been constructed and trained by monitored deformation data and process information associated with interim part geometric information. The proposed method can be generalised for different parts with certain similarities and has the potential to provide a reference for an adaptive machining control strategy for reducing part deformation. The proposed method was validated by actual machining experiments, and the results show that the prediction accuracy has been improved compared with existing methods. Furthermore, this paper shifts the difficult problem of residual stress measurement and off-line deformation prediction to the solution of on-line deformation prediction based on deformation monitoring data.

Analysis of Manufacturing Technology of Composite Materials in Light Sport Aircraft

Light sport aircraft generally refers to single-seat or two-seat light aircraft with a take-off weight of less than 600 kg. With the characteristics of simple structure and low price, it has developed rapidly in recent years. One of the key points in the design and manufacture of light sport aircraft is to reduce the cost of structure manufacture. Therefore, composite materials are widely used. It not only reduces the weight of aircraft structure, but also reduces the cost. Combined with the structural characteristics of light sport aircraft, the material manufacturing process is analyzed, and the application of different processes in light sport aircraft is compared to determine the best manufacturing process plan.

Deposition Group-based Toolpath Planning for Additive Manufacturing with Multiple Robotic Actuators

Abstract This paper proposes a practical approach for toolpath planning of vector-based additive manufacturing (AM) processes with multiple robotic actuators. It classifies and models the operational spatial constraints of possible actuator collisions and indexes the deposition priorities of materials. The contours within each layer of a multi-material object are sorted according to material deposition priorities, material distribution on the actuators, and the spatial constraints for collision avoidance. The sorted contours are then arranged into a series of deposition groups for subsequent concurrent fabrication. The proposed approach has been incorporated into a virtual prototyping system for visualization and validation of AM processes with various types of robotic actuators. Case studies show that it can greatly improve the concurrency of material deposition, and hence reduce the build time of complex multi-material and large single-material objects substantially. It can be practically adapted for control of AM processes with multiple robotic actuators.

Intelligent Process Planning for Additive Manufacturing

Abstract This paper introduces an intelligent approach for process planning of additive manufacturing (AM) in digital environment. A global adaptive slicing algorithm is developed and embedded in the introduced concept, which determines the layer thicknesses and widths based on the minimization of the deviations between the CAD model boundary and its stepped approximation. It is discussed that there are different metrics to measure the deviations such as cusp height, cusp volume and surface roughness criteria. A new criterion is developed to globally minimize the overall volumetric deviations of the final product from the desired geometric model. The proposed methodology uses the locally optimized layer thicknesses as the inputs to calculate the globally optimized layer thicknesses and the optimal contour for each layer. The global optimization problem is highly nonlinear that can be solved with a metaheuristic algorithm such as Simulated Annealing.

Activity Modeling of Preliminary Additive Manufacturing Process Planning

This paper presents a Design for Additive Manufacturing (DfAM) approach by focusing on manufacturability, process and resource selection. For this purpose, a novel process and resource selection approach for Additive Manufacturing (AM) is developed in order to investigate simultaneously the manufacturability and the accuracy issues in AM process selection. The proposed approach is presented by an IDEF0 activity model to create the context in which data requirements and data flows are defined for the selection. The preliminary process planning content of this approach covers traditional and AM process selection problem, where the decision maker has to select the most appropriate technology to manufacture the desired product. The following steps will be devoted to AM process planning. Therefore, the most appropriate alternative for fabrication with AM is selected by investigating the criteria as resource specifications and manufacturability analysis, as well as accuracy performance. This evaluation system has been applied as a step-by-step methodology that employs well-known procedures, such as screening, comparative assessment, and ranking process to select the most suitable alternative for production with AM. Finally, the proposed approach is illustrated by an industrial case study, and it provides a DfAM guideline for engineers and researchers in the early phase of the product development process.

Multi-view feature modeling for design-for-additive manufacturing

This paper presents a design-for-additive manufacturing (DfAM) methodology based on multi-view feature modeling. Multi-view feature model is a unified information carrier which contains the data of a product related to different lifecycle stages. The information can be selectively extracted, interpreted and clustered to provide a specific view of the product and thus to facilitate the design-for-X, e.g. manufacturability design with the manufacturing view and mechanical property enhancement with the analysis view. Feature conversion provides a mechanism to translate the lifecycle stage-related descriptions of the product, which therefore reveals the underlying dependencies and addresses the complexities in associative modeling. For instance, manufacturing information has to be extracted to support the construction of the analysis model, because process planning of additive manufacturing (AM) has a direct impact on the material properties. The main benefit of multi-view feature modeling for AM is that integrated product development can be realized to simultaneously take several engineering aspects into account, e.g. concurrent design of the structural mechanical properties and manufacturability. Apparently, performing the integrated design can enhance the overall design quality and significantly improve the product development efficiency. Specifically in this paper, the design, manufacturing, and analysis views of an AM product will be modeled. Level set will be adopted as the basic mathematical tool for multi-view feature modeling because of its compatibility with all the concerned design activities. The effectiveness of the integrated product design will be demonstrated by numerical case studies.

SIMPM – Upper-level ontology for manufacturing process plan network generation

Abstract Distributed computer integrated manufacturing is increasingly adopting cloud computing, software-as-a-service (SaaS) and multi-agent systems as steps towards “design anywhere, build anywhere” strategy. In this scenario, ontologies not only serve as common message exchange structure among distributed agents but also provide reasoning capability to extract implicit knowledge from explicit information already stored in the knowledge base. Foundation ontologies (upper-level), comprised of most general concepts of a domain, provide a common semantic structure to the domain-level ontologies, which capture details of multi-disciplinary manufacturing knowledge. In this paper, novel upper-level ontology, called SIMPM (Semantically Integrated Manufacturing Planning Model), is proposed in order to model three fundamental constraints of manufacturing process planning: variety, time, and aggregation. The philosophical underpinning of the proposed ontology – presented as OWL-DL axioms – is derived from a three dimensional planning model, developed during our past research on computer-aided process planning. As part of the evaluation of SIMPM ontology, we first expound on the interoperability issues with other upper-level manufacturing ontologies. Next, we present a case study on process planning for prismatic part design. In this way, we demonstrate how the generic set of proposed axioms may be used to address various manufacturing process planning concerns, such as alternative manufacturing resources, the temporal order among operations and granularity in the details of a process plan.

Integrated Process Planning and Scheduling of Mechanical Manufacturing

Integrated Process Planning and Scheduling of Mechanical Manufacturing

Linear-Time Thermal Simulation of As-Manufactured Fused Deposition Modeling Components

Like many other additive manufacturing (AM) processes, fused deposition modeling (FDM) process is driven by a moving heat source, and temperature history plays an important role in determining the mechanical properties and geometry of the final parts. Thermal simulation of FDM is challenging due to geometric complexity of manufacturing process and inherent computational complexity which requires numerical solution at every time increment of the process. We describe a new approach to thermal simulation of the FDM process, formulated as an explicit finite difference method that is applied directly on as-manufactured model described by a typical manufacturing process plan. The thermal model accounts for most relevant thermal effects including heat convection and radiation to the environment, heat conduction with build platform and between adjacent roads (and adjacent layers). We show that the proposed simulation method achieves linear time complexity both theoretically and numerically. This implies that the simulation not only scales to handle three-dimensional (3D) printed components of arbitrary complexity but also can achieve real-time performance. The approach is fully implemented, validated against known analytic solutions, and is tested on realistic complex shapes.

Energy Consideration in Machining Titanium Alloys with a Low Carbon Manufacturing Requirements: A Critical Review

Machining of titanium alloys poses a serious challenge for the industry, due to its tendency to work harden during the machining process, high cutting temperatures, high cutting pressures, chatter, and its reactivity with tool materials over 500°C. In conjunction with its low thermal conductivity and low modulus of elasticity, these factors impede the machinability of titanium. This work presents an overview on machining the Titanium Alloy by considering the energy involved in the manufacturing processes in order to have a low carbon manufacturing requirements by evaluating carbon emission in the manufacturing process plan.

The Use of Virtual Manufacturing Features in forward Manufacturing Process Planning

CAPP system is the missing link between CAD/CAM system. Two types of operation of CAPP systems can be distinguished. The first one is the backward process planning, where the part is transformed from its ready state to the stock state. The second method is the forward planning, where the stock is transformed into the finished part. Backward process planning allow for the greater degree of automation, but is difficult for the acceptation among the industrial users. One of the problem in the forward process planning is the necessity to use the manufacturing features which do not occur in the finished part, they occur only in the part intermediate states. The paper propose so called virtual manufacturing features to solve this problem.

IMPlanner-MAS: A Multiagent System for Distributed Manufacturing Process Planning

The paper reports development of the multiagent-based framework for distributed manufacturing process planning. The research builds on previous results in developing intelligent manufacturing planning platform and extends it into agent-based modeling. Both, design and manufacturing tasks are defined as sequences of steps to be performed by highly intelligent autonomous agents. Autonomous agents are classified into two categories: task agents, which are responsible for completing design or manufacturing tasks, and service agents, which provide services for individual steps of those tasks. For multiagent implementation, we have chosen JADE framework and both task agents and service agents have been implemented by extending agents from JADE. Thus, the JADE’s message passing mechanism has been adopted for inter-agent communication and appropriate ontologies for the message passing have been built from planning classes and objects. The brief overview of IMPlanner functionalities has been provided and development and implementation of service agents for several typical manufacturing planning tasks have been explained. The proposed framework has been executed in the context of the simulation model for evaluation of dynamic routing policies.

Multi-agent System for Cloud Manufacturing Process Planning

The fundamental concern of building a distributed Cloud manufacturing (CM) platform is how wide variety of manufacturing services (SaaS, PaaS, HaaS, IaaS) can be integrated under a common cloud platform? More technically, this concern is related to the classical data integration problem, i.e. how to universally map information from heterogeneous data sources. Adoption of CM may become possible if collaborative agents can automatically discover a set of suitable CM services, and invoke them in a particular order to achieve a certain manufacturing task. Cloud computing community suggested semantic web services in order to enable automatic discovery, invocation and orchestration of web services. In this paper, we describe a novel multi-agent framework, where agents are configured based on Belief, Desire, and Intention (BDI) formalism. In this proposed framework, agents are capable of autonomously discovering and orchestrating manufacturing services based on their intrinsic and extrinsic awareness of the manufacturing knowledge at its most contemporary state. The internal structure of agents are constructed by Horn-DL rules, arguing such DL-safe rules will be able to extract and analyze manufacturing knowledge bases, built with OWL-DL. This chapter also introduces a novel method of selecting suitable services, from the intrinsic semantic in Horn-DL rule. This integration of Horn-Dl and semantic cloud services is designed based on a logical extension of Horn-DL.

Recognition and decomposition of rib features in thin-shell plastic parts for finite element analysis

Feature recognition has been extensively studied for applications in computer-aided design (CAD), computer-aided manufacturing, and computer-aided process planning. However, its application in fini...

A non-retraction path planning approach for extrusion-based additive manufacturing

Notwithstanding the widespread use and large number of advantages over traditional subtractive manufacturing techniques, the application of additive manufacturing technologies is currently limited by the undesirable fabricating efficiency, which has attracted attentions from a wide range of areas, such as fabrication method, material improvement, and algorithm optimization. As a critical step in the process planning of additive manufacturing, path planning plays a significant role in affecting the build time by means of determining the paths for the printing head's movement. So a novel path filling pattern for the deposition of extrusion–based additive manufacturing is developed in this paper, mainly to avoid the retraction during the deposition process, and hence the time moving along these retracting paths can be saved and the discontinuous deposition can be avoided as well. On the basis of analysis and discussion of the reason behind the occurrence of retraction in the deposition process, a path planning strategy called “go and back” is presented to avoid the retraction issue. The “go and back” strategy can be adopted to generate a continuous extruder path for simple areas with the start point being connected to the end point. So a sliced layer can be decomposed into several simple areas and the sub-paths for each area are generated based on the proposed strategy. All of these obtainable sub-paths can be connected into a continuous path with proper selection of the start point. By doing this, separated sub-paths are joined with each other to decrease the number of the startup and shutdown process for the extruder, which is beneficial for the enhancement of the deposition quality and the efficiency. Additionally, some methodologies are proposed to further optimize the generated non-retraction paths. At last, several cases are used to test and verify the developed methodology and the comparisons with conventional path filling patterns are conducted. The results show that the proposed approach can effectively reduce the retraction motions and is especially beneficial for the high efficient additive manufacturing without compromise on the part resistance.

Production and maintenance planning optimisation in biopharmaceutical processes under performance decay using a continuous-time formulation: A multi-objective approach

This work addresses the optimal planning of biopharmaceutical continuous manufacturing processes under performance decay, modelling its operational constraints in a mixed integer linear programing (MILP) model, based on a Resource Task Network (RTN) continuous single-time grid formulation. The model assesses the manufacturing constraints for the determination of the production schedule while defining the appropriate maintenance planning timing in downstream units to assure optimal process performance. An improved model approach is discussed and compared with the application results to literature-based industrial cases. In order to evaluate different solutions towards the multiple decision maker’s strategic and operational objectives, the definition of the Pareto sets for three bi-objective analyses is performed with the augmented ε-constraint method, using the profit maximisation: with the minimisation of the number of intermediate maintenance operations, the maximisation of average service level, and the maximisation of the utilisation rate of processing units.

Manufacturing process information modeling using a metamodeling approach

Information integration and interoperability among different design and manufacturing application software systems are important in smart manufacturing implementation and product life cycle management. Information models are foundational and critical to the specification of common terms, interfaces, and software architectures for information interoperability. The manufacturing process is one of the key processes in a product life cycle. This paper presents a methodology of using the metamodels as the modeling basis in manufacturing process information modeling. A manufacturing process information metamodel (MPIMM), which consists of object classes, relationship classes, and relationships, defines the information and relationships of processes, operations, resources used, and product/part manufactured of manufacturing process planning. The MPIMM is built by unified modeling language (UML) while the semantics of the process elements and their attributes are specified referencing the process specification language. A four-layer framework is proposed to construct manufacturing process information model (MPIM) following the rules of metamodeling, and including meta-metamodeling, manufacturing process information metamodeling, and manufacturing process domain information modeling; thus, manufacturing process plan data can be represented. The UML profile extension mechanism realized by defining Stereotype, TaggedValue, and Constraint is used in extending MPIMM to MPIM. A case study of applying MPIM in the product life cycle data management system for port hoisting equipment manufacturing is provided to demonstrate and verify the modeling capability and efficiency of the proposed methodology. This work provides a systematic and standardized modeling methodology and information expression mechanism for manufacturing process information.

A Heuristic Approach to Solve an Industrial Scalability Problem

In recent years, the rapid change of market demand is increasing the need for scalability as a key characteristic of manufacturing systems. Scalability allows production capacity to be rapidly and cost-effectively reconfigured in different situation with different requirements and constraints. Our industrial partners are facing quarterly scalability problems involving a multi-unit and multi-product manufacturing system. In this paper, an original approach is presented to solve this kind of problems. Starting from the original manufacturing system configuration and process plan, a set of practical principles are introduced to seek for the feasible configurations; a GA is designed to search in the global solution space. A balancing objective function is defined and used to rank the proposed configurations. A real case study with 4-unit / 4-product situation demonstrates both the validity and efficiency of the proposed approach.