Setup Planning Research Articles

A nested partitioning-based approach to integrate process planning and scheduling in flexible manufacturing environment

Set-up planning is an important step in manufacturing a part type, and it can be used to integrate the manufacturing functions of process planning and scheduling. While considering the problem from optimisation perspective, set-up planning involves several issues such as grouping the features, tool approach direction (TAD) and machining operations. Here, we have considered the minimisation of total manufacturing cost, makespan and maximisation of the machine utilisation to obtain an optimal set-up plan while satisfying all the constraints. The cross-machine adaptive set-up planning (ASP) for a part is a nested partition (NP)-hard problem with flexible machining resources. Also, its impact on the integration of process planning and scheduling is a crucial step. The NP-based approach, which partitions the solution space, selecting the most promising region according to the formulated objective function, is adapted and reported in this article. This approach clusters the computational effort in the most promising region and also generates an exact optimal solution for underlying various set-up planning. The proposed algorithm has been tested by taking an illustrative example, and the results are compared with genetic algorithm. Further, five diverse scenarios are studied to prove the efficiency of the proposed approach.

An automatic fixture modeling system using search strategy

Fixtures are critical part of both traditional and modern manufacturing operations. The time allocated to the design and manufacture of these components significantly impacts production cycle time and can improve the quality of current and future products, and therefore, significant consideration is required to design fixture and their applications in manufacturing. In this article, design of an automatic modular fixture modeling system is proposed for prismatic components. The proposed system consists of fixture planning, fixture layout, and fixture assembly modules. The process and setup plans are used as input into the system. A rule-based system is developed to assign suitable locating scheme to locate and clamp datum for fixture planning phase. The search strategy is designed to select the locating and clamping points based on geometric and functional constraints. The final fixture assembly is achieved using standard fixture components and CATVBA editor using CATIA V5 as the platform. The graphical fixture database is constructed using commercial fixture components from manufacturers such as Fixture Works and Carrlane. The proposed methodology is successfully validated with multiple case studies.

An optimization approach to biorefinery setup planning

As the production of first generation biofuels from corn or rape seed is facing severe criticism due to the perceived competition with food production, second generation biofuels made from non-food biomass are being developed to fill the gap. These can be made from lignocellulosic residues instead of agricultural products, which is commonly considered to make competition for soils and land-use change less severe. Economic competitiveness for this kind of biofuels could however not be established so far for various reasons, such as complex and expensive plant technology and the need of biomass transportation to the plant. In contrast to large fossil plants, economies of scale are overcompensated by increasing specific biomass transportation cost for large biorefineries. In order to suitably approximate these effects, a nonlinear optimization model is presented in this paper to simultaneously identify optimal plant setups and capacities. In this model, the co-production of other hydrocarbon products in addition to fuels in biorefineries through different combinations of Fischer–Tropsch product upgrading processes is considered. As the optimal plant capacity also depends on the economic value of the plant's products, several biorefinery process setups and their corresponding process-specific economies of scale are compared with regard to their economic viability.

An integrated setup planning and fixture design system for prismatic parts

This paper reports a knowledge–based system for conceptual and layout modular fixture design developed on an intelligent CAD system, ICAD. The integration of setup planning and fixture design is achieved through conceptual fixture design which includes two stages: the pre–setup and post–setup conceptual design. In the pre–setup stage, the system takes feature–based part models as input and generates feasible fixturing features for each possible setup based on static constraints only. This information is then used by a setup planning system developed separately. Post–setup conceptual fixture design takes place when the setup plan is available. For each setup with its intermediate workpiece state, the surface candidates for each fixturing datum are identified and ranked according to various geometric and technological constraints. The best ranked surface for each fixturing datum is selected. The system then performs layout design by generating all the supporting, locating and clamping points for each setup, taking into account various constraints including part geometry, stability, modular fixture elements, and interference. The series of setups are simulated graphically on the computer screen. Output from this system can be used for detailed fixture design. In this paper, the development of the system is described in detail and a case study is presented to highlight its performance.

An intelligent process planning system for micro turn-mill parts

An attempt has been made to develop a generalised system for the generation of process plan for the manufacture of micro parts in this work. It has two components; first one deals with automatic part feature extraction from feature-based model and second one performs the execution of process planning activities in accordance with feature using knowledge-based system approach. The proposed system maps extensible markup language (XML) data for the feature based-model and produces the corresponding manufacturing activities needed for the manufacture of micro parts. The process plan modules considered in this work includes process sequence, tools and fixtures, process parameters selection and set-up plan generation. An attempt has been made to develop process parameters selection module based on experimental investigation and optimisation apart from manufacturing catalogues and user manuals. Feature extraction through XML files avoids complex feature extraction process. The application of the developed system has been verified with a case study. The present system is limited to micro turn-mill features. Incorporation of more micro features and consideration of other activities of process plan ensures a complete process planning system for micro-machining processes.

Status of the MLLTRAP setup and future plans

The MLLTRAP Penning trap system serves as a development environment, both for mass spectrometry as well as for novel in-trap decay-spectroscopy experiments at the MATS facility at FAIR. This contribution gives an outline on the development work done at MLLTRAP and presents the current status.

A graph-based ant colony optimization approach for process planning.

The complex process planning problem is modeled as a combinatorial optimization problem with constraints in this paper. An ant colony optimization (ACO) approach has been developed to deal with process planning problem by simultaneously considering activities such as sequencing operations, selecting manufacturing resources, and determining setup plans to achieve the optimal process plan. A weighted directed graph is conducted to describe the operations, precedence constraints between operations, and the possible visited path between operation nodes. A representation of process plan is described based on the weighted directed graph. Ant colony goes through the necessary nodes on the graph to achieve the optimal solution with the objective of minimizing total production costs (TPC). Two cases have been carried out to study the influence of various parameters of ACO on the system performance. Extensive comparative experiments have been conducted to demonstrate the feasibility and efficiency of the proposed approach.

Integration of process planning and scheduling through adaptive setup planning: a multi-objective approach

The integration of process planning and scheduling is considered here as a multi-objective optimisation problem in reconfigurable manufacturing settings where more than one machines (3-axis, 4-axis and 5-axis machine configurations) are available to manufacture a part. In this research, machining features are grouped according to tool approach direction considering the criteria such as makespan, machining cost and machine utilisation. We have also addressed adaptive characteristics of process plan associated with setup i.e. a cross-machine setup planning to capture the different configuration of machines. To solve this type of multi-objective problem, a meta-heuristic, non-dominated sorting algorithm (NSGA-II) is applied to take into account the computational intractability of the problem. Further, a fuzzy set theory approach is developed to extract one of the Pareto-optimal solutions as the best compromising one. Illustrative examples are trialled to demonstrate the capability of the proposed model. The results confirm that the proposed multi-objective optimisation model gives robust performance in developing optimal adaptive setup plan.

Automated process planning system: A new method for setup planning and a mathematical model for fixture design

Setup planning and fixture design are two main tasks for the integration of design and manufacturing process. Setup planning identifies which features must be machined in each setup and determines locating datum for each setup, whereas fixture planning determines precise locating and rigid clamping of workpieces according to a part design and process requirements. So, a close interaction exists between setup planning and fixture design. This research deals with the problems of setup and fixture planning for the machining of prismatic parts. In the first step, a new heuristic method is presented to plan the setups with accurate respect to datum faces in design and manufacturing. Two concepts, namely, “inferiority face” and “control face,” have been used for this purpose. In the next step, a mathematical model is used to define the primary, secondary and tertiary fixture planes with respect to locators’ position. This model determines relationship between misplacement of locators and dimensional and geometrical specifications of workpiece. The main purpose of developing the model is to determine the effect of locator height error on hole position tolerance. The capability of this model is verified by simulation in “motion study” module in SolidWorks software. This approach is very useful in the hole-making process. The system is developed in Visual Basic on a SolidWorks platform. The effectiveness of the system is verified by an industrial component.

Software Development for Setup Planning of Rotational Part

An innovative approach was developed to solve the problem of setup planning, which is the most critical problem in process planning for discrete metal parts. Setup planning is the act of preparing detailed work instructions for setting up a part. The major objective of this research is to improve the performance of CAPP systems by developing a systematic approach to generate practical setup plans based on tolerance analysis. A comprehensive literature review on tolerance control in CAPP was conducted. It was found that tolerance chart analysis, a traditional tolerance control technique, is reactive in nature and can be greatly improved by solving the problem of setup planning. In order to develop a theoretically sound foundation for tolerance analysis-based setup planning, the problem of tolerance stack up in NC machining was analyzed in terms of manufacturing error analysis. Guidelines for setup planning were then developed based on the analysis. To systematically solve the setup planning problem, a graph theoretical setup planning algorithm for rotational parts was then developed for automated and integrated setup planning and fixture design. Its efficiency and effectiveness evaluated. The result is promising. The algorithms were then computerized. A setup planning program was developed under the Microsoft Windows environment using C.

SU-E-T-547: Influence of Phantom Voxel Size Setup On Monte Carlo Simulation in Gamma Knife Using EGSnrc

Purpose: To investigate the influence of different phantom voxel size setup on the accuracy and efficiency when conducting Monte Carlo simulation of Gamma knife using EGSnrc. Methods: We simulated a 30mmκ60mmκ60mm size uniform water phantom and locate the phantom isocenter 70.6mm vertical down to the source in accord with measured condition for all different models. Dose calculation was executed within two different x direction voxel size setup schemes. One is completely according to measured intervals, which were 0.1mm big for all 300 voxels and the other is to divide voxels into 5 parts after picking two penumbra sections with 2mmκ4,0.5mmκ9,1mmκ5,0.5mmκ9,2mmκ4. After phantom voxel partition, Gamma Knief simulation and dose calculation, center cross section lateral profiles along X direction could be obtained for those two voxel size setup plans using EGSnrc. Those two plan profiles were plotted and compared with measured data respectively. Results: Results showed that great satisfaction can be achieved between profiles designed in 5 parts and measured data for all models. Differences can be reduced from as max as 8% for designed in measured intervals to less than 3% for designed in 5 parts compared with measured data respectively. It only takes 1/3 of designed in measured intervals time for phantom setup in 5 parts, with less than 15 mins for every simulation. Conclusion: Deviding phantom voxels into 5 parts can make it more accurate and effective when conducting Monte Carlo simulation of Gamma knife using EGSnrc. Project 30970866 supported by National Natural Science Foundation of China

Realising process planning and scheduling integration through adaptive setup planning

Setup planning is one of the crucial exercises that affects process planning, scheduling and their integration. In a reconfigurable environment where more than one machine is available to process a part, setup planning assumes an important position which involves a complex optimisation problem facing several constraints. In this research machining features are sequenced and grouped into certain setup based on tool approach direction (TAD). Therefore considering the criteria such as machine utilisation, cost and makespan, near optimal solutions are selected to satisfy the requirements of the scheduling system. We have also addressed in this paper adaptive characteristics of process plan associated with setup, i.e. a cross machine setup planning to capture the different configuration of machines. Exploiting the stress of the immune system, a well known intelligent search technique known as artificial immune system (AIS) has been applied to solve two problems associated with the research issue discussed here. The proposed AIS based approach is demonstrated to resolve an example problem. It is found that the proposed approach is successfully applicable to machines having several configurations and accommodative to different setup requirements from a scheduling system where the frequent changes in machines are witnessed. By the way of combining the setup for alternative machines with process planning, we can demonstrate clearly a true relation of integration of functionalities of process planning and scheduling.

Pallet operation sequencing based on network part program logic

Abstract CAPP systems play a relevant role in aiding planners during setup planning, operation sequencing and pallet configuration activities. The support and automation granted by these techniques, together with the use of non-linear process planning logic, lead to a reduction in the planning time and costs, thus making manufacturers more competitive. This paper presents an approach that integrating process and production planning leads to the definition at the shop-floor level of the optimal operation sequence to machine all of the workpieces on a pallet using a four-axis machine tool. Part programs of non-production movements for each possible sequence of two operations are automatically generated at the shop-floor level and are simulated to obtain the non-production time. The complete sequence of operations is then defined on the basis of the minimisation of the estimated non-production time. This minimisation is performed using a mathematical model that defines a good sequence of operations. Four algorithms are adopted to analyse the proposed solution and to reduce the gap from optimality. The approach is tested on some cases taken from literature and on a real case. The real case was provided by a company that produces mechanical components. The obtained results underline a reduction on production and planning time, and consequently an increment in the company profit.

Fixture and Setup Planning and Fixture Configuration System

By automating the tasks of the fixture design and configuration we can save considerable time, and spare the process engineer from a tiresome work. In this paper a system is introduced that gives us recommendations on the number and the order of the needed setups, and proposals on the appropriate fixtures needed at machining a given workpiece. The input data are the CAD model of the workpiece saved in IGES format, and the technological requirements. The output data are the CAD models of the needed fixtures.

Based on region division setup planning for sheet metal assembly in aviation industry

The task of setup planning is to determine the number and sequence of setups and the machining features or operations in each setup. Due to the locating method’s character, the position of the locators may keep away joining tools from arriving at joining points during the joining process of sheet metal. In order to solve these problems, a novel method is proposed, which consists of three parts: (1) the points on the skin are divided into sets of supplied riveting and prior riveting points by convex hull generating method; (2) fixture vector is defined, and a suitable fixture region is generated by vector multiplication; and (3) the particle swarm optimization algorithm is applied to generate optimal setup scheme by setting up the parameters. The new setup planning approach can accomplish riveting work by minimum setup times and workpiece variation without finite element analysis software. At last, a certain kind of aircraft wing joining process is illustrated as an example to demonstrate the effect of the proposed approach.

Automated setup planning in CAPP: a modified particle swarm optimisation-based approach

Comprehensive process planning is the key technology for linking design and the manufacturing process and is a rather complex and difficult task. Setup planning has a basic role in computer-aided process planning (CAPP) and significantly affects the overall cost and quality of machined parts. This paper presents a generative system and particle swarm optimisation algorithm (PSO) approach to the setup planning of a given part. The proposed approach and optimisation methodology analyses constraints such as the TAD (tool approach direction), the tolerance relation between features and feature precedence relations, to generate all possible process plans using the workshop resource database. Tolerance relation analysis has a significant impact on setup planning to obtain part accuracy. Based on technological constraints, the PSO algorithm approach, which adopts the feature-based representation, optimises the setup planning using cost indices. To avoid becoming trapped in local optima and to explore the search space extensively, several new operators have been developed to improve the particles’ movements, combined into a modified PSO algorithm. A practical case study is illustrated to demonstrate the effectiveness of the algorithm in optimising the setup planning.

Computing Axes of Rotation for Setup Planning Using Visibility of Polyhedral Computer-Aided Design Models

This paper presents a method for determining feasible axes of rotation for setup planning, based on the visibility of a polyhedral model. The intent of this work was to develop a feature-free approach to setup planning, with the specific focus on multi-axis machine setups. Visibility mapping can provide a quantitative evaluation of a surface, a feature or an entire part model; however, the next step is to use this information for process planning. In this paper, we present an approach of using a visibility map to evaluate axes of rotation that could be used in an indexer-type setup on a machine tool. Instead of using expensive and complicated multi-axis machining, it may be feasible to machine using multiple three-axis toolpaths if a single axis of rotation can be used to rotate the part through the minimum set of orientations. An algorithm is presented that is capable of processing visibility information from a polyhedral model; hence, the method is generic and does not require feature detection. As such, the work is applicable to a variety of applications; in particular for subtractive rapid prototyping where complex geometry may not contain recognizable features.

GENERATION OF OPTIMAL SEQUENCE OF MACHINING OPERATIONS IN SETUP PLANNING BY GENETIC ALGORITHMS

This paper aims at automatic generation of optimal sequence of machining operations in setup planning by Genetic Algorithm (GA) based on minimizing the number of setup changes and tool changes, subject to various machining precedence constraints. The GA has been reconstructed as the method of representing an operation is not as simple as assigning it a binary digit as in case of a chromosome in traditional GA but it has to be a distinct real number. Accordingly, the GA operators had to be modified. At the end of each GA cycle, there might be chromosomes having high fitness values but not conforming to constraints. Moreover, due to randomness of GA, the conformable chromosomes might tend to get lost. In order to minimize such losses, the elitist model is used for selection of chromosomes. Furthermore, a special subroutine has been developed to check the chromosomes for conformability and modify/repair those that violate the constraints.

Setup Planning Automation for Six-Axis Wire Electrical Discharge Machining

A modern six-axis wire electrical discharge machining (WEDM) system is capable of producing more complex geometries than 2D, 2½D, or ruled surface parts. The rotational axis on a six-axis WEDM system allows a part to be rotated while using a cutting wire to fabricate it. However, limited automation for process planning six-axis WEDM systems requires significant time and effort must be put into process planning. Even with commercially-available computer-aided design (CAD) software, it is difficult to produce process plans for a six-axis WEDM system. Toward automatic development of process plans, a method of determining such setup plans, including the number of setup orientations and rotational axis movements, is presented in this paper. Tangent visibility analysis results presented in our prior research are used to guide the setup, and intermediate coordinate systems are defined in order to classify the tangent visibility results. A greedy algorithm is developed to determine the set of intermediate coordinates and setup orientations for six-axis WEDM.

An integrated setup/fixture planning approach for machining prismatic parts

Setup/fixture planning for machining prismatic parts is usually carried out by grouping features/operations into setups, determining suitable locating surfaces for each setup, and sequencing setups and operations in each setup. The presently developed setup/fixture planning methods can be classified into three categories: multi-constraints, fixture driven, and tolerance analysis planning methods. The multi-constraints planning is theoretically sound, but very difficult to use. In fixture driven planning, the generated setup plans are highly practical, but may not be optimal. Tolerance analysis based planning cannot be used to generate the optimal solution by itself. In this research, a new integrated setup/fixture planning approach is developed to identify the optimal and practical setup/fixture plan. The planning is conducted in four steps. (1) The dissimilarity degree matrix (DDM), operation precedence graph (OPG), and hybrid graph are used to describe the requirements and constraints for setup/fixture planning. (2) A setup precedence graph (SPG) is used to describe precedence constraints between setups. The SPG is generated by the vertex clustering algorithm. Precedence loops among setups are avoided by checking whether two serial vertex clusters can generate a loop. (3) Suitable locating surfaces are selected for each setup in a SPG. When the fixture locating surface and design datum surface are different, two types of dimension recalculations are employed to obtain the dimensions against the locating surfaces. (4) All the candidate setup/fixture plans are evaluated based on the number of setups and recalculation of dimensions. An example is given to demonstrate the effectiveness of the developed approach.