Rule and branch-and-bound algorithm based sequencing of machining features for process planning of complex parts

The machining sequence of machining features is vital to achieve efficient and high quality manufacturing of complex NC machining parts. In most feature-based process planning system, the machining features are sequenced as the lowest level unit. However, a single machining feature of complex parts such as aircraft structural parts is usually machined by multiple machining operations. The one-to-many mappings between the machining features and the machining operations cause the increase of the non-cutting tool path. In order to solve this problem, some types of machining features of complex parts are decomposed into several sub-machining features that are associated with a single machining operation individually according to the rules which are abstracted from the machining process of complex parts. Benefitting from the decomposition, the sub-machining features from different machining feature can be assembled into a sub-machining feature in order to avoid the cutting tool marks. The different types of sub-machining features are sequenced in the light of some rules which are also extracted from the machining process of complex parts. And the branch-and-bound algorithm are employed to sequence the same type sub-machining features to minimum the non-cutting tool path. A pilot feature-based process planning system has been developed based on this research, and has been used in some aircraft manufacturers in China.     

IKOOPPS: an intelligent knowledge-based object-oriented process planning system for the manufacture of progressive dies

Abstract: This article describes an intelligent knowledge-based object-oriented process planning (IKOOPP) system for the manufacture of progressive die plates. A die assembly is designed using a variety of standardised components based on a computer-aided design (CAD) system. A feature recognition module extracts all the pertinent geometrical properties and functional attributes of each machining feature from the CAD representation models. These properties and attributes are converted into an object-oriented representation. Knowledge of the functions of the machining feature allows process planning information to be automatically deduced. Specialised tool engineering knowledge are formulated as production rules or procedures to establish the required set of cutting tools, together with the machining allowances and sequence of operations.     

A constraint-based operation sequencing for a knowledge-based process planning

Process planning is a decision-making process. Decisions on machining operations for a particular feature have to be made on various independent conditions such as which operation should be performed with which tools and under what cutting parameters. An integrated knowledge-based CAPP system called ProPlanner has been developed. The system has five modules namely information acquisition, feature recognition, machining operation planning and tool selection, set-up planning, and operation sequencing. Most process-planning systems do not produce alternative process plans. Usually, a fixed sequence created by a process plan is not necessarily the best possible sequence. Therefore, the aim should be to generate all possible operation sequences and use some optimality criteria to obtain the best sequence for the given operating environment. This paper presents an efficient heuristic algorithm, belongs to the system's operation sequencing module, for finding near-optimal operation sequences from all available process plans in a machining set-up. The costs of the various machining schemes are calculated and the machining scheme with the lowest cost is chosen. All feasible cutting tools are identified for each particular feature and the corresponding machining operations. This process is repeated for all the features in the machining set-up. All possible feature sequence combinations allowed by the current feature constraints are then generated. Appropriate cutting tools are identified and assigned to different operations. The feature sequence with the smallest number of tool changes is adopted.     

A novel 0-1 linear integer programming model for dynamic machine-tool selection and operation allocation in a flexible manufacturing system

This paper considers a problem of dynamic machine-tool selection and operation allocation with part and tool movement policies in a flexible manufacturing system (FMS) environment. For this purpose, a novel 0-1 linear integer programming model is presented in such a way that each part and each tool can move during the production phase. It is assumed that there are a given set of tools and machines that can produce different kinds of orders (or part types). The objective of this model is to determine a machine-tool combination for each operation of the part type by minimizing some production costs, such as machining costs, setup costs, material handling costs and tool movement costs. In addition, due to the NP-hard nature of the problem, a new heuristic method based on five simple procedures (FSP) is proposed for solving the given problem, whose performance is tested on a number of randomly generated problems. The related results are compared with results obtained by a branch-and-bound method. It has been found that the proposed heuristic method gives good results in terms of objective function values and CPU times.     

An integrated framework of tool path planning in 5-axis machining of centrifugal impeller with split blades

Centrifugal impeller is a complex part commonly used in aerospace, energy, and air-conditioning industries. Its manufacture involves multi-axis free form machining, a time consuming and error-prone process. Tool path planning is considered a critical issue in the process but still lacking of systematic solutions. This paper proposes a tool path planning framework for 5-axis machining of centrifugal impeller with split blades. It provides several CAM functions that assist the users to generate collision-free cutter motions with smooth tool orientations. First, the machining process is divided into four operations and the planning tasks of each operation are standardized. Second, the hub surfaces are properly decomposed, re-grouped, and re-parameterized to facilitate calculation of quality tool path with reduced cutter retraction and plunging. Finally, geometric algorithms are developed to automatically detect tool collisions and then correct the erroneous tool orientations. An optimization scheme is applied to minimize the total amount of tool posture changes after the correction. An impeller is machined with the NC codes generated from the framework. The result shows the effectiveness of this work in automating the tool path planning in 5-axis machining of highly intricate impeller.     

Drilling reconfigurable machine tool selection and process parameters optimization as a function of product demand

Special purpose machines (SPMs) are customized machine tools that perform specific machining operations in a variety of production contexts, including drilling-related operations. This research investigates the effect of optimal process parameters and SPM configuration on the machine tool selection problem versus product demand changes. A review of previous studies suggests that the application of optimization in the feasibility analysis stage of machine tool selection has received less attention by researchers. In this study, a simulated model using genetic algorithm is proposed to find the optimal process parameters and machine tool configuration. During the decision-making phase of machine tool selection, unit profit is targeted as high as possible and is given by the value of the following variables: SPM configuration selection, machining unit assignment to each operation group, and feed and cutting speed of all operations. The newly developed model generates any random chromosome characterized by feasible values for process parameters. Having shown how the problem is formulated, the research presents a case study which exemplifies the operation of the proposed model. The results show that the optimization results can provide critical information for making logical, accurate, and reliable decisions when selecting SPMs.     

Optimization of multi-task turning operations under minimal tool waste consideration

Most of the literatures on machining economics problems tend to focus on single cutting operations. However, in reality most parts that need to be machined require more than one operation. In addition, machining technology has been developed to the point that a single computer numerical control (CNC) machine is capable of performing multiple operations, even simultaneously, employing multiple spindles and cutting tools. When several operations are performed on a CNC turning machine, various tools are required for the cutting operations. Determining the life of these cutting tools under different machining conditions is an arduous task for the operators. They usually replace the tools based on their experience or according to the specific cutting tool handbook. Frequent tool replacements may result in wasted tools and tool utilization, while infrequent tool replacements may result in poorly machined parts. In this study we propose a mathematical model in which several different turning operations (turning, drilling, and parting) with proper constraints are performed. The issue of tool replacement is taken into account in the proposed cutting model. In addition, an evolutionary strategy (ES)-based optimization approach is developed to optimize the cutting conditions of the multiple turning-related operations while taking into account the minimizing unit cost criteria under the economical tool replacement strategy.     

Process selection for the design of aluminum components

This paper describes a method for process selection of aluminum components in the early stages of design. Aluminum has many advantages in a variety of applications in its manufacturability and recyclability. Yet, engineers who are trained to design steel components do not take full advantage of this material. The main reason is that engineers tend to be unaware of the many economical processing methods for aluminum. We have developed a program that combines preliminary screening of processes with normalized cost analysis. Design compatibility analysis (DCA) ranks each process based on its feasibility with the basic geometry, material, and production requirements. For top candidates, the program employs external cost routines for detailed comparisons. The primary processes considered are extrusion, sheet forming, forging, die casting, and sand casting. The program extends its compatibility and cost analysis to secondary operations such as bending and machining. The program should be useful for engineer training and as a preliminary design tool. The program uses HyperCard as a front-end, Prolog for logic-based analysis, and Excel for cost calculations.     

Flexible robotic demanufacturing using real time tool path generation

The need for new demanufacturing technologies exists due to a growing population of end of life electronic products. The demanufacturing method presented in this work is unique from disassembly because destructive methods are employed; thus, eliminating the need to account for precedence relationships. Furthermore, the new demanufacturing method employs cutting operations but differs from traditional machining operations due to the degree of flexibility required. To address this very high scale flexibility, a unique prototype flexible demanufacturing work cell has been established. Unique contributions of this flexible demanufacturing method include a new system model that utilizes a product surface model and a robot tool position model to actively generate real time tool paths. The model uses manifolds to reduce the tool path generation function to navigation of the surface manifold. Tool path generation occurs in three stages: machining operation sequencing, active tool path generation and active product avoidance. A case study of the demanufacture of mobile phones is presented to illustrate the flexible robotic demanufacturing operation. The case study shows that a new flexible robotic demanufacturing process has been achieved that requires no predetermined information on the product surface geometry.     

Intelligent Programming of CNC Turning Operations using Genetic Algorithm

CAD/CAM systems are nowadays tightly connected to ensure that CAD data can be used for optimal tool path determination and generation of CNC programs for machine tools. The aim of our research is the design of a computer-aided, intelligent and genetic algorithm(GA) based programming system for CNC cutting tools selection, tool sequences planning and optimisation of cutting conditions. The first step is geometrical feature recognition and classification. On the basis of recognised features the module for GA-based determination of technological data determine cutting tools, cutting parameters (according to work piece material and cutting tool material) and detailed tool sequence planning. Material, which will be removed, is split into several cuts, each consisting of a number of basic tool movements. In the next step, GA operations such as reproduction, crossover and mutation are applied. The process of GA-based optimisation runs in cycles in which new generations of individuals are created with increased average fitness of a population. During the evaluation of calculated results (generated NC programmes) several rules and constraints like rapid and cutting tool movement, collision, clamping and minimum machining time, which represent the fitness function, were taken into account. A case study was made for the turning operation of a rotational part. The results show that the GA-based programming has a higher efficiency. The total machining time was reduced by 16%. The demand for a high skilled worker on CAD/CAM systems and CNC machine tools was also reduced. Received: September 2004 / Accepted: September 2005     

Hybrid cutting simulation via discrete vector model

Geometric cutting simulation and verification play an important role in detecting NC machining errors in mold and die manufacturing, thereby reducing the correcting time and cost on the shop floor. According to workpiece model, current researches may be categorized into view-based, solid-based, and discrete vector-based methods. Each methodology has its own strengths and weaknesses in terms of computing speed, representation accuracy, and its ability to perform numerical inspection. This paper proposes a cutting simulation methodology via a hybrid workpiece model which consists of the general discrete vector model and its simplified model. Workpiece modeling scheme, cutting simulation via tool swept surface modeling and vector intersection, and some case studies of mold and die machining are presented in this paper.     

Polygon subdivision for pocket machining process planning

This paper presents a new approach to improve tool selection for arbitrary shaped pockets based on an approximate polygon subdivision technique. The pocket is subdivided into smaller sub-polygons and tools are selected separately for each sub-polygon. A set of tools for the entire pocket is obtained based on both machining time and the number of tools used. In addition, the sub-polygons are sequenced to eliminate the requirement of multiple plunging operations. In process planning for pocket machining, selection of tool sizes and minimizing the number of plunging operations can be very important factors. The approach presented in this paper is an improvement over previous work in its use of a polygon subdivision strategy to improve the machining time as well as reducing the number of plunges. The implementation of this technique suggests that using a subdivision approach can reduce machining time when compared to solving for the entire polygonal region.     

A hole-machining process planning system for marine engines

This study proposes a hole-machining process planning system for marine engines, which converts industrial field requirements to the rules of the system. Unlike a fully automated system, the proposed system satisfies the requirements effectively by allowing the user to choose and to edit the rules. A computer-aided process planning (CAPP) system is comprised of Hole Manager, Cutting Sequence Definition, and Operation Manager which are derived from the conventional knowledge based system. For the purpose of efficiently coordinating the system operations, a procedure is proposed as: (a) defining priorities for each operation, using properties for the nested cutting, the number of tool changes, the directions of the tool, the tool diameter, and the hole height, (b) calculating the score for each operation with the related priority level, and (c) sorting of operations by the score in an ascending order. This idea is quite simple but yields a significant efficiency along with a high flexibility. By changing the priority of elements, various operation sequences can be obtained. The proposed method also considers multi-axis machining and the use of special attachments. This paper describes the construction of a practical hole-making CAPP system that satisfies the specific requirements of marine engine machining. The applied examples are machined by using the proposed system, including an engine block and a cylinder header.     

Optimal tool selection for pocket machining in process planning

In process planning for pocket machining, selection of tool size, tool path, cutting width at each tool path, and calculation of machining time are very important factors for optimal process planning. The tool size is the most important factor because the other factors depend on tool size. Therefore, the optimal selection of tool size is the most essential task in pocket machining process planning. This paper presents a method for selecting optimal tools for pocket machining for the components of injection mold. The branch and bound method is applied to select the optimal tools which minimize the machining time by using the range of feasible tools and the breadth-first search.     

Minimizing the number of stations and station activation costs for a production line

In the problem under study, a paced unidirectional machining line, consisting of a number of stations, has to be configured to produce parts of several types. A given set of operations is required for each part type and the same operation can be required for different part types. Re-assignment of operations, when switching from one part type to another, is not allowed. All operations assigned to the same station are performed simultaneously. The objective is to assign operations to stations in order to minimize the number of stations and the station activation costs, with respect to precedence and zoning constraints. The two objectives are considered in a lexicographic order, the former being the primary objective. Activation costs refer to the costs induced by the energy consumption, equipment maintenance, setup activities or labor requirement which occur whenever a station is used. Computational complexity for various special cases is established. Heuristic algorithms, integer linear programming formulations, and computer experiments are presented. Instances of practical dimension, with 40–80 operations, are solved in an hour on a conventional computer.     

An exact solution to the TLP problem in an NC machine

This paper considers a job sequencing problem for a single numerical controlled machining center. It is assumed that all the considered jobs must be processed on a single machine provided with a tool magazine with C positions, that no job requires more than C tools to be completely machined and that the tools may be loaded and unloaded from the tool magazine only when the machining operations for each job are completed. The decisional problem is referred to as the tool loading problem (TLP) and it determines the jobs machining sequence as well as the tools to load in the machine tool magazine before the machining operations on each job may start. In industrial cases where the tool switching time is both significant relative to job processing time and proportional to the number of tool switches, the performance criterion is the minimization of the number of tool switches. This paper demonstrates that the TLP is a symmetric sequencing problem. The authors enrich a branch-and-bound algorithm proposed in literature for the TLP with the new symmetric formulation. Computational experiments show the significant improvement obtained by the novel symmetric formulation of the TLP.     

Optimal and collision free tool posture in five-axis machining through the tight integration of tool path generation and machine simulation

The generation of collision free NC-programs for multi-axis milling operations is a critical task, which leads to multi-axis milling machines being exploited below their full capacities. Today, CAM systems, generating the tool path, do not take the multi-axis machine movements into account. They generate a multi-axis tool path, described by a sequence of tool postures (tool tip+tool orientation), which is then converted by a NC-postprocessor to a machine specific NC-program. As the postprocessing is normally done in batch mode, the NC-programmer does not know how the machine will move and the chance for having collisions between (moving) machine components is often very high. The execution of a machine test run or the application of a machine simulation system (NC-simulation) is the only solution to inform the NC-programmer about possible machine collisions during operation.This paper describes a multi-axis tool path generation algorithm where the tool orientation is optimised to avoid machine collisions and at the same time to maximise the material removal rate along the tool track. To perform efficient collision avoidance, the tool path generation module (traditional CAM), the postprocessing (axes transformation) and machine simulation has been integrated into one system. Cutting tests have been carried out to define the allowable tool orientation changes for optimisation and collision avoidance without disturbing the surface quality.The developed multi-axis tool path generation algorithm is applicable for the machining of several part surfaces within one operation. This, together with tool path generation functionality to adapt the tool orientation for both, maximal material removal and avoidance of collisions between (moving) machine components, are the innovative aspects of the presented research work.     

PATH: a work sampling-based approach to ergonomic job analysis for construction and other non-repetitive work

A high prevalence and incidence of work-related musculoskeletal disorders have been reported in construction work. Unlike industrial production-line activity, construction work, as well as work in many other occupations (e.g. agriculture, mining), is non-repetitive in nature; job tasks are non-cyclic, or consist of long or irregular cycles. PATH (Posture, Activity, Tools and Handling), a work sampling-based approach, was developed to characterize the ergonomic hazards of construction and other non-repetitive work. The posture codes in the PATH method are based on the Ovako Work Posture Analysing System (OWAS), with other codes included for describing worker activity, tool use, loads handled and grasp type. For heavy highway construction, observations are stratified by construction stage and operation, using a taxonomy developed specifically for this purpose. Observers can code the physical characteristics of the job reliably after about 30 h of training. A pilot study of six construction laborers during four road construction operations suggests that laborers spend large proportions of time in nonneutral trunk postures and spend approximately 20% of their time performing manual material handling tasks. These results demonstrate how the PATH method can be used to identify specific construction operations and tasks that are ergonomically hazardous.     

An integrated CAPP/CAM system for stamping die pattern machining

Since the early 1980s, CAPP has been expected to bridge the gap between CAD and CAM. Though numerous research works on CAPP have been reported, it is not easy to find a commercial CAPP system applicable to complicated objects with freeform shapes such as mold and die. The dependency on CAM system is holding one leg of CAPP, while the complexity of the solution space in freeform shape machining has a tight grip on the other. This paper exemplifies that these obstacles on the CAPP bridge can be overcome by the integration with CAM and by focusing on a specific application area. Major components of a staming die for the car body panel are manufactured by machining the raw stock castings, which are usually made by the lost foam casting process. Die pattern is the lost foam pattern made of Styrofoam for the raw stock casting. The industry trend is to build die patterns by CNC machining. In this paper, a highly specialized CAPP/CAM integrated system, called Generative Pattern Machining (GPM), for automatic tool paths generation to cut die pattern from the CAD model of the stamping die is described. The overall structure and the detailed steps of GPM are explained. GPM is being used by DaimlerChrysler pattern shop very successfully.     

Process planning optimization for parallel drilling of blind holes using a two phase genetic algorithm

Determining the optimal process parameters and machining sequence is essential in machining process planning since they significantly affect the cost, productivity, and quality of machining operations. Process planning optimization has been widely investigated in single-tool machining operations. However, for the research reported in process planning optimization of machining operations using multiple tools simultaneously, the literature is scarce. In this paper, a novel two phase genetic algorithm (GA) is proposed to optimize, in terms of minimum completion time, the process parameters and machining sequence for two-tool parallel drilling operations with multiple blind holes distributed in a pair of parallel faces and in multiple pairs of parallel faces. In the first phase, a GA is used to determine the process parameters (i.e., drill feed and spindle speed) and machining time for each hole subject to feed, spindle speed, thrust force, torque, power, and tool life constraints. The minimum machining time is the optimization criterion. In the second phase, the GA is used to determine the machining sequence subject to hole position constraints (i.e., the distribution of the hole locations on each face is fixed). The minimum operation completion time is the optimization criterion in this phase. Simulation results are presented to demonstrate the effectiveness of the proposed algorithm in solving the process planning optimization problem for parallel drilling of blind holes on multiple parallel faces. In order to evaluate the performance of proposed algorithm, the simulation results are compared to a methodology that utilizes the exhaustive method in the first phase and a sorting algorithm.