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.

Throughput Optimization In Robotic Cells provides practitioners, researchers, and students with up-to-date algorithmic results on sequencing of robot moves and scheduling of parts in robotic cells. It brings together the structural results developed over the last 25 years for the various realistic models of robotic cells. This book is ideally suited for use in a graduate course or a research seminar on robotic cells.

Interval robotic cells with several processing stages (chambers) have been increasingly used for diverse wafer fabrication processes in semi-conductor 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.

Various systems science and engineering disciplines are covered and challenging new research issues in these disciplines are revealed. They will be extremely valuable for the readers to search for some new research directions and problems. Chapters are contributed by world-renowned systems engineers Chapters include discussions and conclusions Readers can grasp each event holistically without having professional expertise in the field

We consider the problem of scheduling operations in bufferless robotic cells that produce identical parts using either single-gripper or dual-gripper robots. 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. Obtaining an efficient algorithm for an optimum k-unit cyclic solution (k ≥ 1) has been a longstanding open problem. For both single-gripper and dual-gripper cells, the approximation algorithms in this paper provide the bestknown performance guarantees (obtainable in polynomial time) for an optimal cyclic solution. We provide two algorithms that have a running time linear in the number of machines: for single-gripper cells (respectively, dual-gripper cells), the performance guarantee is 9/7 (respectively, 3/2). The domain considered is free-pickup cells with constant intermachine travel time. Our structural analysis is an important step towardr esolving the complexity status of finding an optimal cyclic solution in either a single-gripper or a dual-gripper cell. We also identify optimal cyclic solutions for a variety of special cases. Our analysis provides production managers valuable insights into the schedules that maximize productivity for both single-gripper and dual-gripper cells for any combination of processing requirements andphysical parameters.

We consider the problem of scheduling operations in a robotic cell processing a single part type. Each machine in the cell has a one-unit input buffer and a one-unit output buffer. The machines and buffers are served by one single gripper robot. The domain considered is free-pickup cells with additive intermachine travel time. The processing constraints specify the cell to be a flow shop. 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 throughput. Bufferless robotic cells have been studied extensively in the literature. However, the few studies of robotic cells with output buffers at each machine have shown that the throughput can be improved by such a configuration. We show that there is no throughput advantage in providing machine input buffers in addition to output buffers. The equivalence in throughput between the two models has significant practical implications, since the cost of providing additional buffers at each machine is substantial.

We consider the problem of scheduling operations in bufferless 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 rate. The robot can be moved in simple cycles that produce one unit or, in more complicated cycles, that produce multiple units. Because one-unit cycles are the easiest to understand, implement, and control, they are widely used in industry. We analyze one-unit cycles for a class of robotic cells called constant travel-time robotic cells. We complete a structural analysis of the class of one-unit cycles and obtain a polynomial time algorithm for finding an optimal one-unit cycle. Constant travel-time robotic cells are used in real manufacturing operations that the authors have encountered during their interactions with companies. The results and the analysis in this paper offer practitioners (i) a tool to experiment with and study the design of a proposed robotic cell during a prototyping exercise, (ii) a lower bound on the throughput of a robotic cell to help them make an informed assessment of the ultimate productivity level, and (iii) a benchmark throughput level (for comparison purposes) for robotic cells whose operations differ slightly from those discussed in this paper.

In many applications, robotic cells are used in repetitive production of identical parts. A robotic cell contains two or more robot-served machines. The robot can have single or dual gripper. The cycle time is the time to produce a part in the cell. 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 steadystate cycle time to produce a part, or equivalently the maximization of the throughput rate. The purpose of this paper is to 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 (or productivity 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.

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.

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.