Dual-gripper Robot Research Articles

Look-ahead based reinforcement learning for robotic flow shop scheduling

Scheduling of a robotic flow shop, where a dual-gripper robot transports parts between machines, is addressed with a makespan measure. Most previous studies on robotic flow shop scheduling have focused on cyclic scheduling where the robot repeats a certain sequence to process identical parts. Recently, noncyclic scheduling of robotic flow shops is strongly required due to the need for producing customized products and smaller order sizes efficiently. This study therefore considers noncyclic scheduling of a dual-gripper robotic flow shop with a given part sequence and proposes a novel solution approach, look-ahead based reinforcement learning (LARL). The LARL consists of deep Q-learning for training a Q-network based on a given set of instances and the look-ahead search used for testing new instances. The look-ahead search in the LARL is efficient, especially for robotic flow shop scheduling where future state information can be used for determining the current robot task. The experimental results comparing the LARL with an optimal algorithm and the well-known robot task sequence show the effectiveness of the LARL.

Scheduling a dual gripper material handling robot with energy considerations

Robotic cells are serial production systems that consist of a number of machines and a material handling robot that transfers parts between the machines. Energy consumption of a robot during its move between two machines can be decreased by carefully selecting its speed. This paper presents models and algorithms that make robot speed and robot activity sequencing decisions together for a dual-gripper robot that can handle two parts simultaneously. We consider both robot energy consumption and cycle time objectives so that a decision maker can observe the trade off between energy cost and throughput rate of the system, and select the best solution among alternatives. Computational experiments demonstrate that proposed approaches can generate efficient solutions for practical size instances, and speed control can significantly conserve energy.

Time minimization in flexible robotic cells considering intermediate input buffers: a comparative study of three well-known problems

ABSTRACTFlexible manufacturing cells are widely used in many real-life industries. These cells contain a group of highly automated machines, the input station, and the output station that are interconnected by a robot which handles the materials, automatically. The system repeats a cycle in its long run, and the cycle time depends on the order of the loading/unloading activities which are performed by the robot. To achieve the most efficient use of these cells, order of the robot activities must be determined. This study is motivated by such a real life system with intermediate machine buffers. First, a mathematical model is presented. Then, to decrease the solution time, a modification of the model is proposed. Additionally, another model is proposed to find the maximum processing time of the machines when the cycle time is known. An assignment problem method is utilized to optimize the cyclic production, and performances of all the proposed methods are examined using several numerical instances. Finally, the performance of the considered system is compared with no intermediate machine buffers system, and also it is compared with the system utilizing a dual-gripper robot. The results show that performances of the three robotic cells are non-identical in practice.

A review of recent theoretical development in scheduling dual-gripper robotic cells

A robotic cell is a set of machines or processing centres served by a robot or a set of robots. Robotic cells can be classified by certain physical and operating characteristics such as robot type (single- or dual-gripper), robot travel-time (constant, additive or Euclidean) and types of parts processed (no-wait, interval processing time or free-pickup). Robotic cells are used in automated manufacturing systems where jobs or parts are produced in a typical flow shop type environment. A significant research effort has been directed towards analysing the problem of robot move sequencing in robotic cells served by single- or dual-gripper robot. In this review paper, we examine the recent theoretical developments on the analysis of throughput optimisation in robotic cells served by a dual-gripper robot. We focus on the problem of scheduling operations in dual-gripper robotic cells that produce identical parts. The objective is to find a cyclic sequence of robot moves that minimises the long-run average time to produce a part or, equivalently, maximises the throughput. The goals of this review paper are to: (i) provide a discussion of existing structural analysis, algorithmic and complexity results for robotic cells under conditions that are common in practice and (ii) present a set of open problems and future research directions. In addition to reporting recent results for dual-gripper robotic cell scheduling problems, we provide insight into a class of cyclic sequences that are not considered in practice but can improve throughput.

Pure cycles in two-machine dual-gripper robotic cells

Abstract We consider a robotic cell served by a dual-gripper robot that consists of identical CNC machines placed linearly and a material handling robot loading/unloading the machines and transporting the parts between them. Identical parts are to be processed in this system and the CNC machines are capable of performing all the operations that a part requires. We consider the problem of sequencing activities of the robot in order to maximize the throughput rate. As a consequence of the flexibility of the CNC machines, a new class of robot move sequences, named as pure cycles, arises. In a pure cycle, the robot loads and unloads each machine once and each part is processed on exactly one of the machines. Thereby, the problem is to determine the best pure cycle that maximizes the throughput rate. We first determine the feasibility conditions for the pure cycles and prove some basic results that reduces the number of feasible pure cycles to be investigated. We analyze 2-machine robotic cells in detail and prove that five of the cycles among a huge number of feasible pure cycles dominate the rest. We determine the parameter regions in which each of the five cycles is optimal. We also analyze the performance improvement that can be attained by using a dual gripper robot and provide managerial insights.

Productivity Improvement From Using Machine Buffers in Dual-Gripper Cluster Tools

Cluster tools (also referred to as robotic cells) are extensively used in semiconductor wafer fabrication. We consider the problem of scheduling operations in an m -machine cluster tool that produces identical parts (wafers). Each machine is equipped with a unit-capacity input buffer and a unit-capacity output buffer. The machines and buffers are served by a dual-gripper robot. Each wafer is processed on each of the m machines, and the objective is to find a cyclic sequence of robot moves that minimizes the long-run average time to produce a part or, equivalently, maximizes the throughput. We first obtain a tight upper bound on the optimal throughput and then use this bound to obtain an asymptotically optimal sequence under conditions that are common in practice. Next, we quantify the improvement in productivity that can be realized from the use of unit-capacity input and output buffers at the machines. Finally, we illustrate our analysis on cluster tools with realistic parameters, based on our work with a Dallas-based semiconductor equipment manufacturer.

Throughput optimization in dual-gripper interval robotic cells

Interval robotic cells with several processing stages (chambers) have been increasingly used for diverse wafer fabrication processes in semiconductor manufacturing. Processes such as low-pressure chemical vapor deposition, etching, cleaning and chemical-mechanical planarization, require strict time control for each processing stage. A wafer treated in a processing chamber must leave that chamber within a specified time limit; otherwise the wafer is exposed to residual gases and heat, resulting in quality problems. Interval robotic cells are also widely used in the manufacture of printed circuit boards. The problem of scheduling operations in dual-gripper interval robotic cells that produce identical wafers (or parts) is considered in this paper. The objective is to find a 1-unit cyclic sequence of robot moves that minimizes the long-run average time to produce a part or, equivalently, maximizes the throughput. Initially two extreme cases are considered, namely no-wait cells and free-pickup cells; for no-wait cells (resp., free-pickup cells), an optimal (resp., asymptotically optimal) solution is obtained in polynomial time. It is then proved that the problem is strongly NP-hard for a general interval cell. Finally, results of an extensive computational study aimed at analyzing the improvement in throughput realized by using a dual-gripper robot instead of a single-gripper robot are presented. It is shown that employing a dual-gripper robot can lead to a significant gain in productivity. Operations managers can compare the resulting increase in revenue with the additional costs of acquiring and maintaining a dual-gripper robot to determine the circumstances under which such an investment is appropriate. [Supplementary materials are available for this article. Go to the publisher's online edition of IIE Transactions for the following supplemental resources: Proofs of all theoretical results, a table summarizing these results, a summary of Algorithm FindCycle, and the Levner–Kats–Levit Algorithm.]

Throughput Optimization in Constant Travel‐Time Dual Gripper Robotic Cells with Parallel Machines

Constant travel‐time robotic cells with a single gripper robot and with one or more machines at each processing stage have been studied in the literature. By contrast, cells with a dual gripper robot, although more productive, have so far received scant attention, perhaps due to their inherent complexity. We consider the problem of scheduling operations in dual gripper robotic cells that produce identical parts. The objective is to find a cyclic sequence of robot moves that minimizes the long‐run average time to produce a part or, equivalently, maximizes the throughput. We provide a structural analysis of cells with one or more machines per processing stage to obtain first a lower bound on the throughput and, subsequently, an optimal solution under conditions that are common in practice. We illustrate our analysis on two cells implemented at a semiconductor equipment manufacturer and offer managerial insights for assessing the potential productivity gains from the use of dual gripper robots.

Scheduling dual gripper robotic cell: One-unit cycles

We consider the scheduling problem of cyclic production in a bufferless dual-gripper robot cell processing a family of identical parts. The objective is to find an optimal sequence of robot moves so as to maximize the long-run average throughput rate of the cell. While there has been a considerable amount of research dealing with single-gripper robot cells, there are only a few papers devoted to scheduling in dual-gripper robotic cells. From the practical point of view, the use of a dual gripper offers the attractive prospect of an increase in the cell productivity. At the same time, the increase in the combinatorial possibilities associated with a dual-gripper robot severely complicates its theoretical analysis. The purpose of this paper is to extend the existing conceptual framework to the dual-gripper situation, and to provide some insight into the problem. We provide a notational and modelling framework for cyclic production in a dual-gripper robotic cell. Focusing on the so-called active cycles, we discuss the issues of feasibility and explore the combinatorial aspects of the problem. The main attention is on 1-unit cycles, i.e., those that restore the cell to the same initial state after the production of each unit. For an m-machine robotic cell served by a dual-gripper robot, we describe a complete family of 1-unit cycles, and derive an analytical formula to estimate their total number for a given m. In the case when the gripper switching time is sufficiently small, we identify an optimal 1-unit cycle. This special case is of particular interest as it reflects the most frequently encountered situation in real-life robotic systems. Finally, we establish the connection between a dual-gripper cell and a single-gripper cell with machine output buffers of one-unit capacity and compare the cell productivity for these two models.

Minimizing the cycle time in serial manufacturing systems with multiple dual-gripper robots

Robots are being used more and more extensively as material-handling systems for automated manufacturing systems. This is especially true for dual-gripper robots whose in-process buffer (the robot's second gripper) constitutes a further element of flexibility. When the number of stations to be served is high and the set of activities the robot must execute is great, the system throughput may depend on robot capability rather than on process times. In such conditions, the use of several robots leads to an increase in system productivity. Obviously, the design and the management of such a handling system becomes more complex: the minimum number of robots required, the work stations to be served by each of them and the robot move cycles must be all determined so as to minimize the cycle time of a multi-robot serial system. Since the aim of minimizing the cycle time could lead to a non-univocal configuration, a secondary objective may be pursued. To this aim, the classic case of a single dual-gripper robotic cell is preliminarily revisited, using a practical rather than a theoretical approach, to show that, under the conditions of minimum cycle time, it is possible to take into account both the reduction of the WIP and that of the length of the transitory periods.

Scheduling Multiple Parts in a Robotic Cell Served by a Dual-Gripper Robot

A robotic cell—a manufacturing system widely used in industry—contains two or more robot-served machines, repetitively producing a number of part types. In this paper, we consider scheduling of operations in a bufferless dual-gripper robotic cell processing multiple part types. The processing constraints specify the cell to be a flowshop. The objective is to determine the robot move sequence and the sequence in which parts are to be processed so as to maximize the long-run average throughput rate for repetitive production of parts. We provide a framework to study the problem, and address the issues of problem complexity and solvability. Focusing on a particular class of robot move sequences, we identify all potentially optimal robot move sequences for the part-sequencing problem in a two-machine dual-gripper robot cell. In the case when the gripper switching time is sufficiently small, we specify the best robot move sequence in the class. We prove the problem of finding an optimal part sequence to be strongly NP-hard, even when the robot move sequence is specified. We provide a heuristic approach to solve the general two-machine problem and evaluate its performance on the set of randomly generated problem instances. We perform computations to estimate the productivity gain of using a dual-gripper robot in place of a single-gripper robot. Finally, we extend our results for the two-machine cell to solve an m-machine problem.

Scheduling Multiple Parts in a Robotic Cell Served by a Dual-Gripper Robot

A robotic cell - manufacturing system widely used in industry - contains two or more robot-served machines, repetitively producing a number of part types. In this paper, we consider scheduling of operations in a bufferless dual-gripper robotic cell processing multiple part types. The processing constraints specify the cell to be a flowshop. The objective is to determine the robot move sequence and the sequence in which parts are to be processed so as to maximize the long-run average throughput rate for repetitive production of parts. We provide a framework to study the problem, and address the issues of problem complexity and solvability. Focusing on a particular class of robot move sequences, we identify all potentially optimal robot move sequences for the part-sequencing problem in a two-machine dual-gripper robot cell. In the case when the gripper switching time is sufficiently small, we specify the best robot move sequence in the class. We prove the problem of finding an optimal part sequence to be strongly NP-hard, even when the robot move sequence is specified. We provide a heuristic approach to solve the general two-machine problem and evaluate its performance on the set of randomly generated problem instances. We perform computations to estimate the productivity gain of using a dual-gripper robot in place of a single-gripper robot. Finally, we extend our results for the two-machine cell to solve an m-machine problem.

Scheduling in dual gripper robotic cells for productivity gains

We consider single part-type problems. Since all parts produced are identical, it is sufficient to determine the sequence of moves performed by the robot. The processing constraints define the cell to be a flowshop. The objective is the minimization of the steady-state cycle time to produce a part, or equivalently the maximization of the throughput rate. We study the problem of scheduling robot moves in dual gripper robot cells functioning in a bufferless environment. We develop an analytical framework for studying dual gripper robotic cells and examine the cycle time advantage of using a dual gripper rather than a single gripper robot. It is shown that an m-machine dual gripper robot cell can have at most double the productivity of its single gripper counterpart. We also propose a practical heuristic algorithm to compare productivity for given cell data. Computational testing of the algorithm on realistic problem instances is also described.