Tool Magazine Research Articles

Reliability analysis of chain tool magazine based on improved FMECA

Reliability analysis of chain tool magazine based on improved FMECA

FCE-based health status evaluation and IGM-based failure prediction of tool magazine manipulator for CNC machine tools

The reliability of machine tool components, particularly the tool magazine manipulator, significantly affects the overall performance of the machine tool. To address the challenge of accurately evaluating the manipulator’s health status using a single performance indicator, this study proposes a method that combines Fuzzy Comprehensive Evaluation (FCE) and a Combined Weighting Method (CWM). By considering both subjective and objective factors, this method provides a comprehensive evaluation of the manipulator’s health status, enhancing the accuracy and reliability of the assessment. The method utilizes fuzzy distribution to construct membership matrices for different health levels and adopts the CWM that combines the Entropy Weight Method (EWM) and Analytic Hierarchy Process (AHP) to determine the combined weights of the health evaluation indices. This approach improves the accuracy and reliability by considering multiple indicators and objectively weighting them based on their importance. The current health status of the manipulator is evaluated using the fuzzy weighted average operator and the maximum membership principle. Moreover, a fault prediction method based on Particle Swarm Optimization (PSO) and GM(1,1) is proposed to overcome the information gap and small sample problems. The proposed model’s prediction accuracy is verified by comparing it with other models, demonstrating its effectiveness and reliability.

A user-friendly toolkit to select and design multi-purpose grippers for modular robotic systems

Robotic grasping is a billion-dollar industry with significant growth potential for the next decade. Unsurprisingly, technology providers and integrators are increasingly assisting in optimising production efficiency by implementing industrial robots and the necessary end-effectors into production lines. However, still too often in today’s robotic applications, dedicated grippers are designed to perform single tasks therewith adversely increasing cycle times and robot cell spaces due to constantly switching grippers from a tool magazine. In order to reduce handling costs and to cope with mass customisation, versatile grasping of various objects with multi-purpose grippers is key in evolving to modular assembly systems.Nowadays, thoughtful selection and design of robotic grippers is still mainly restricted to expert knowledge due its ad hoc and multi-objective nature. However, gripper selection and design should be tailored to the properties of the objects to be grasped, and the tasks to be executed. As a result, current solutions often end up being partly appropriate and/or over-dimensioned. The use of software tools to support this complex decision-making process is needed but limited so far.This paper presents a user-friendly toolkit that assists in selecting appropriate robotic grippers for grasping pre-specified ranges of objects. For this, a web API has been established for accessing the available gripper database and selection methodology. Additionally, this toolkit assists in designing multi-functional jaws for impactive grippers, and lay-outing individually positioned astrictive grippers. The underlying optimiser will try to find the most ideal grasping points on each object in accordance with quality metrics and constraints, and this for each of the selected grippers. To demonstrate the functionality of the presented toolkit, two case studies on impactive and astrictive gripper designs have been worked out involving 3D mechatronic and 2D sheet metal parts.

Optimum Scheduling of a Multi-Machine Flexible Manufacturing System Considering Job and Tool Transfer Times without Tool Delay

In order to minimize makespan (Cmax) without causing tool delay with the fewest copies of each tool type, this study investigates the concurrent scheduling of automated guided vehicles (AGVs), machines (MCs), tool transporter (TT), and tools in a multi-machine flexible manufacturing system (FMS). The tools are housed in a central tool magazine (CTM), accessible to and utilized by several machines. AGVs and the tool transporter (TT) move jobs and tools between machines. Since it involves allocating tool copies and AGVs to job operations, sequencing job operations on machines, and related trip operations, such as AGVs’ and TT’s empty trip and loaded trip times, this simultaneous scheduling problem is highly complicated. This issue is resolved using the symbiotic organisms search algorithm (SOSA), based on the symbiotic interaction strategies that organisms adapt to survive in the ecosystem. This study proposes a mixed nonlinear integer programming formulation to address this problem. Verification is performed using an industrial problem from a manufacturing organization. The results show that employing two copies for two tool types out of 22 tool kinds and one copy for the remaining tool types results in no tool delay, which causes a reduction in the Cmax as well as cost. The industries that can benefit directly from this study are consumer electronics manufacturers, original equipment manufacturers, automobile manufacturers, and textile machine producers. The results demonstrate that the SOSA provides promising results compared to the flower pollination algorithm (FPA).

Multi-objective hierarchical clustering for tool assignment

Due to the limited tool magazine capacities of CNC machines, time-consuming tool changeovers result in inefficient equipment utilization. This study provides a method to minimize the changeovers by optimizing the allocation of the tools to the machines. The proposed algorithm is efficient as it approaches the tool assignment task as a multi-objective hierarchical clustering problem where the products are grouped based on the similarity of the tool demands. The novelty of the goal-oriented agglomerative clustering algorithm is that it is based on the Pareto optimal selection of the merged clusters. The applicability of the method is demonstrated through an industrial case study. The tool assignment problem has also been formulated as a bin-packing optimization task, and the results of the related linear programming were used as a benchmark reference. The comparison highlighted that the proposed method provides a feasible solution for large real-life problems with low computation time.

Modeling the sequence of part machining to minimize the time spent on the machining center, considering the working tool changing

An algorithm for choosing a rational sequence for machining a part on a machine with a tool magazine is proposed using the drilling operations example. The algorithm is based on the analysis of all possible options and the calculation of the time spent on each of them. In this respect, the working tool (drill) change is considered, if it is necessary to switch to another machining type (drilling a different diameter hole). Three types of time costs are included in the calculation of the total machining time for one part: the duration of each operation, the duration of the transition to the next operation, and the duration of the working tool change. The result of the algorithm application is the sequence of machining the part with the least total time spent on transitions to the machining areas and the working tool changing.

Asset Administration Shells in Tool Lifecycle Monitoring

In order to use tools, e.g. in machining, efficiently until the end of their life, predictions for the remaining tool lifespan are essential. These can only be made based on comprehensive life cycle data of the individual tools originating on different machines. Current approaches usually pursue a machine-related monitoring of the process data; a tool-related evaluation is thus not possible. The concept of the Asset Administration Shell (AAS), defined by Plattform Industrie 4.0, allows not only storing information but also describing it semantically so that interpretation is possible without a priori knowledge. They are thus suitable for making systems interoperable and can be used in the scenario described to manage the lifecycle data of tools. The AAS of a tool can move from one host to another together with the described tool and collect or provide data at the machine. A central server can be used to manage tools that are in storage and are used on any machine without a corresponding management capability. When a tool is removed from the tool magazine, the AAS is transferred to a central server where the tool information can be retrieved and from which the administration shell can be requested the next time the tool is used. While an exchange format is defined for the AAS, the necessary communication mechanisms for exchange between the central server and machines or machine-related devices must be defined. A registry in which all AAS are listed allows applications, such as an overarching user interface or an AI-based forecasting algorithm, to find the administration shells of all tools and access the individual data. The complete use case has been implemented exemplarily utilizing a central server and Sinumerik edge devices close to the machine tool.

Parallel Scheduling of Machines, Tool Transporter and Tools in a Multi Machine FMS with Alternative Routing Using Flower Pollination Algorithm

Scheduling jobs and tools is a significant problem for manufacturing systems. Inefficient job scheduling and tool loading planning may result in the underutilization of capital-intensive machines and a high machine idle time. Tools are transferred by a tool transporter (TT) between machines. Therefore, efficient scheduling of jobs, TT, and the tools with alternate machines enables a manufacturing system to increase machines’ utilization and decrease their idle times. This paper addresses machines, TT, and tools concurrent scheduling with alternate machines and only one copy of every tool variety is made available where the tools are costly, in a multi-machine flexible manufacturing system, taking into account tool transfer times for makespan (MS) minimization. The tools are placed in a central tool magazine, which shares and serves them to many machines to cut down the price of duplicating the tools in each machine. The problem is to assign machines from alternate machines, tools, and corresponding TT trips, including the deadheading trip and loaded trip, to job operations for MS minimization. This paper uses a nonlinear mixed-integer programming framework to present the problem, and a flower pollination algorithm (FPA) is employed to solve it. The results show that FPA outperforms the Jaya algorithm, and the usage of alternate machines for the operations reduces the MS. Reduction in MS indicates an improvement in utilization of resources.

Development of scheduling methodology in a multi-machine flexible manufacturing system without tool delay employing flower pollination algorithm

This paper addresses machines, automated guided vehicles (AGVs), tool transporter (TT), and tools concurrent scheduling in a multi-machine flexible manufacturing system (FMS) for makespan minimization. The fewest number of copies of each tool type is employed to prevent tool delays, and job and tool shift times between machines are taken into account. The tools are placed in a central tool magazine (CTM), which shares and serves them to many machines to cut down the price of duplicating the tools in each machine. This simultaneous scheduling problem is challenging to solve because it entails determining the fewest tool copies of each tool kind without tool delay, assigning AGVs and tool copies to job-operations (jb-ons), ordering jb-ons on machines, and related trip operations such as deadheading and loaded flight times for both TT and AGVs. This paper uses a mixed-integer nonlinear programming (MINLP) framework to present the problem, and a flower pollination algorithm (FPA) is employed to solve it. For verification, a manufacturing company’s industrial problem is employed. The results show that employing two copies each for two tool types and one copy each for the remaining tool types causes no tool delay, reduction in makespan and cost, and the FPA outperforms the Jaya algorithm.

Optimum scheduling of machines, automated guided vehicles and tools without tool delay in a multi‐machine flexible manufacturing system using symbiotic organisms search algorithm

AbstractThis article deals with machines, automated guided vehicles (AGVs) and tools simultaneous scheduling in multimachine flexible manufacturing system (FMS) with the lowest possible number of copies of every tool type without tool delay considering jobs' transport times among machines to minimize makespan (MSN). The tools are kept in a central tool magazine (CTM), which is shared by and serves many machines. Tool transporter (TT) and AGVs shift tools and jobs among machines respectively. This concurrent scheduling problem is extremely complex in nature as it involves determining the lowest possible tool copies of every type of tool, allocation of AGVs and tools copies to job‐operations, job‐operations sequencing on machines, and associated trip operations including the dead heading trip and loaded trip times of AGVs. This paper proposes nonlinear mixed integer programming (MIP) formulation to model this problem and symbiotic organisms search algorithm (SOSA) for solving this problem. Verification is carried out using an industrial problem in a manufacturing firm. The results show that employing two copies for one tool type and one copy each for the remaining tool types results in no tool delay and reduction in MSN which causes a reduction in cost, and SOSA is providing better solution than Jaya algorithm.

Design and Development of a Flexible Manufacturing System

Abstract: In most organizations, a flexible manufacturing system (FMS) is concerned with the automatic production of different parts in the middle range because it is flexible. In a nutshell, it's a machine that makes everything. FMS relies heavily on the flow of jobs and tools in order to function. The FMS work centre can handle a large number of tasks at once. For FMS facilities, a tool magazine is in use as a means of reducing tool inventory. We present the Jaya method in this work to schedule tasks and tools simultaneously without considering tool transfer delays across machines; this is what we call the make span goal. On numerous make span-related challenges, the suggested heuristic is evaluated and compared with current approaches. The suggested heuristic beats the already used approaches, according to the findings. Keywords: “Flexible Manufacturing System”, “Automation” performance, Manufacturing, flexibility

Minimization of Number of Tool Switching Instants in Automated Manufacturing Systems

This study addresses the problem of minimizing tool switching instants in automated manufacturing systems. There exist a single machine and a group of jobs to be processed on it. Each job requires a set of tools, and due to limited tool magazine capacity, and because it is not possible to load all available tools on the machine, tools must be switched. The ultimate goal, in this framework, is to minimize the total number of tool switching instants. We provide a mathematical programming model and two constraint programming models for the problem. Because the problem is proven to be NP-hard, we develop two heuristic approaches, and compare their performance with methods described in the literature. Our analysis indicates that our constraint programming models perform relatively well in solution quality and execution time in small-sized problem instances. The performance of our greedy approach shows potential, reaching the optimal solution in 82.5% of instances. We also statistically demonstrate that the search algorithm enhances the quality of the solution obtained by the greedy heuristic, particularly in large sets. Hence, the solution approach, i.e., the greedy heuristic and the search algorithm proposed in this study is able to quickly reach near-optimal solutions, showing that the method is appropriate for manufacturing settings requiring sudden adjustments.

Simultaneous Scheduling of Machines and Tools in a Multi-Machine FMS with Alternate Machines Using Crow Search Algorithm

Scheduling jobs and tools is a significant problem for manufacturing systems. Inefficient job scheduling and tool loading planning may result in under utilization of capital intensive machines and a high level of machine idle time. Therefore, efficient scheduling of jobs and tools enables a manufacturing system to increase machines’ utilization and decrease their idle times. This paper addresses machines’ and tools’ joint scheduling with alternate machines in a multimachine flexible manufacturing system (FMS) to minimize makespan (MSN). Only one copy of each type of tool is made available in FMS where tools are expensive. The tools are stored in the central tool magazine (CTM), which shares and serves them to several machines in order to reduce the cost of duplicating the tools in every machine. The problem is to select machines from alternate machines for job-operations, allocation of tools to the job-operations and job-operations’ sequencing on machines for MSN minimization. This paper presents nonlinear mixed integer programming (MIP) formulation to model this simultaneous scheduling problem and crow search algorithm (CSA) built on the crows’ intelligent behavior for solving this problem. The results show that CSA is providing better solutions than Jaya algorithm and the usage of alternate machines for the operations can reduce MSN.

Optimization of Cutting Tool Allocation to Enhance Workload Balance and Total Completion Time in Parallel-Type FMS

This study aims to build a machine scheduling method that involves the cutting tool management in parallel-type flexible manufacturing systems. These systems consist of multi-axis CNC machine tools and are equipped with an automated tool changer and a large-capacity tool magazine. The target scheduling problem could be described as a multi-objective parallel scheduling problem. We consider the availability of cutting tools stored in the magazine as so-called “machine eligibility,” and propose a two-phase scheduling method for tool allocation and job sequencing on machines to minimize the workload balance between machines and the total completion time. Two mathematical models for tool allocation are provided: a machine-eligibility-based model and an enhanced version of the model that considers each cutting tool. A series of computational experiments demonstrates the effectiveness of the proposed method. We also clarify the relationship between schedule performance measures and job routing flexibility in the system.

A MBD Model-driven Automatic Generation Method of On-machine Measuring Program for CNC Machining

Aiming at the problem that the programming of on-machine measurement in CNC machining process is heavily dependent on operators and the efficiency is lower, a MBD model-driven automatic generation method of on-machine measuring program is proposed. The characteristics of measuring program is analysed and the relationship between the parameters of measuring cycle and the features of MBD model is built. The approach of PMI (product manufacturing information) data identifying and extracting is presented. The scheme for transforming the PMI data and geometric features to measuring cycle parameters is constructed. In order to make the measuring program adapt to the change of probe position which stored in different tool magazine, the way of collecting the position automatically by OPC DA protocol is provided. On the basis of the proposed methods and approaches, an on-machine measuring program generating software system has been developed. The running result of the system is given, and the feasibility and effectiveness of the method were demonstrated.

Integrated simultaneous scheduling of machines, automated guided vehicles and tools in multi machine flexible manufacturing system using symbiotic organisms search algorithm

ABSTRACT This paper deals with machines, automated guided vehicles and tools simultaneous scheduling in multi-machine flexible manufacturing system considering jobs’ transport times among machines to minimize makespan. Only one copy of every tool type is made available due to economic restrictions. The tools are stored in central tool magazine that shares with and serves for several machines. This simultaneous scheduling problem is highly complex in nature as it involves the allocation of automated guided vehicles and tools to job-operations, job-operations sequencing on machines, and associated trip operations including the dead heading trip and loaded trip times of automated guided vehicles. This paper proposes symbiotic organisms search algorithm for solving this problem. An industrial problem in a manufacturing company is used for verification. The results show that SOSA is providing better solutions than Jaya algorithm, and the obtained schedule can be implemented practically with reduction in cost.

Implementation of bi-directional searching Chemical Reaction Optimization (CRO) algorithm towards achieving cutting tool indexing time minimization in Automatic Tool Changer(ATC)

Determining the optimum cutting tool positions in a tool magazine is a challenging task which involves a huge searching space. Reduction of manufacturing time even by nanoseconds will highly be beneficial for all process industries. The prime focus of this research work is to reduce the total turret or tool indexing time in Automatic Tool Changer (ATC) which in turn curtails the idle non-cutting time of the bi-directional turret or tool magazine in a CNC machine. This variant of optimization problem falls under the category of non-deterministic hard polynomial (NP-hard) problem. Chemical Reaction Optimization (CRO) algorithm is proposed to determine the near optimal/global optimal solution with lesser computational cost. Five benchmark case studies are considered in this work to assess the robustness of the proposed algorithm. From the results, it is evident that the proposed algorithm yields solutions which matches or exceeds with the solution quality.

Simultaneous scheduling of machines and tools in a multi machine FMS with alternative routing using symbiotic organisms search algorithm

This paper deals with simultaneous scheduling of machines and tools with alternate machines in a multi machine flexible manufacturing system (FMS) to minimize makespan (MS). Only one copy of each type of tools is made available due to economic restrictions and the tools are stored in a central tool magazine (CTM) that shares with and serves for several machines. The problem is to select machines from alternate machines for job-operations, allocation of tools to job-operations and job-operations’ sequencing on machines for MS minimization. This paper presents a nonlinear mixed integer programming (MIP) formulation to model the combined scheduling of machines and tools with alternate machines and a symbiotic organisms search algorithm (SOSA) built on the symbiotic interaction strategies that organisms employ to continue to exist in the ecosystem for solving the scheduling of machines and tools with alternate machines. The results have been tabulated, analyzed. It is observed that there is a reduction in MS when the alternate machines are considered for job-operation.

Inventory policy and magazine reloading schedule optimisation for cutting tools in pipe manufacturing

In a steel pipe manufacturing industry, several machining centres are used for different purposes, where tool magazines speed up the tool exchange and machine setup. Early tool replacement incurs unutilised tool lives, leading to additional tool purchase. On the other hand, delays in tool replacement may result in sudden tool failure and machine breakdown. A multiple tool holding facility in a tool magazine provides a good opportunity to reduce the number of magazine reloading. However, an increased magazine size eventually leads to an increase in the inventory and operating cost for the tool magazine. To trade-off between the stated conflicting objectives, a non-linear mixed-integer programming problem is formulated to minimise the total cost for cutting tools. The problem is solved both optimally and heuristically to find an appropriate combination of tool ordering size, magazine size and reload timing. The throughput rate is observed to improve when an optimal size of tool magazine is installed. The sensitivity analyses are done to investigate the influence of different parameter(s) on the optimum solution.

An iterated local search procedure for the job sequencing and tool switching problem with non-identical parallel machines

In this paper, a new generalization of the uniform job sequencing and tool switching problem is presented. It considers non-identical parallel machines, which differ in tool magazine capacity and setup times. Applications of the problem can be found in the metal working or semiconductor manufacturing industries when the jobs require different tool sets for processing. The paper provides a Mixed Integer Programming formulation for the job sequencing and tool switching problem with machine-dependent processing and tool switching times under the consideration of three conflicting objectives (minimizing the total flowtime, minimizing the makespan and minimizing the total number of tool switches). Different efficient construction heuristics and Iterated Local Search methods are proposed and evaluated, using 640 new and publicly available instances. The results of the construction heuristics, the Iterated Local Search schemes and a Mixed Integer Programming Solver are discussed. The extensive computational experiments show the merit of the perturbation strategy in order to overcome local optima. It is shown that certain methods are more or less suitable depending on the objective function.