Mehdi Foumani

Scheduling rotationally arranged robotic cells served by a multi-function robot

Automated material handling systems are usually characterised by robotic cells that result in the improvement of the production rate. The main purpose of this research is to study the scheduling of a rotationally arranged robotic cell with the multi-function robot (MFR). This special class of industrial robot is able not only to transfer the part between two adjacent processing stages but also to perform a special operation in transit. Considering MFR for material handling and operation, the objective function of the research here is the maximisation of production rate, or equivalently the minimisation of the steady-state cycle time for identical part production. This problem is modelled as a travelling salesman problem to give computational benefits with respect to the existing solution methods. Then, the lower bound for the cycle time is deduced in order to measure the productivity gain of two practical production permutations, namely uphill and downhill permutations. As a design problem, a preliminary analysis initially identifies the regions where the productivity gain of a regular multi-function robotic cell is more than that of the corresponding single-function robotic cell for both small- and large-scale cells. The conclusion shows the suggested topics for future research.

Notes on Feasibility and Optimality Conditions of Small-Scale Multifunction Robotic Cell Scheduling Problems With Pickup Restrictions

Optimization of robotic workcells is a growing concern in automated manufacturing systems. This study develops a methodology to maximize the production rate of a multifunction robot (MFR) operating within a rotationally arranged robotic cell. An MFR is able to perform additional special operations while in transit between transferring parts from adjacent processing stages. Considering the free-pickup scenario, the cycle time formulas are initially developed for small-scale cells where an MFR interacts with either two or three machines. A methodology for finding the optimality regions of all possible permutations is presented. The results are then extended to the no-wait pickup scenario in which all parts must be processed from the input hopper to the output hopper, without any interruption either on or between machines. This analysis enables insightful evaluation of the productivity improvements of MFRs in real-life robotized workcells.

Scheduling dual gripper robotic cells with a hub machine

This paper introduces a new methodology to optimise the cycle time of dual-gripper robotic workcells. The workcell under study is composed of a group of m production machines. In order to produce a completed part, a chain of m-1 secondary operations are performed by m-1 different machines, and a hub machine is alternately visited for m primary operations. Indeed, parts must reenter the hub machine after any one of secondary operations. Those types of robotics workcells are used for high capacity production such as in photolithography manufacturing, These cells are cluster tools for semiconductor manufacturing where a wafer visits a processing stage several times for the atomic layer deposition (ALD) processes. For electroplating lines, these cells are also common in practice where there is a multifunction production stage that is visited by parts over once. This optimisation methodology is limited to the dual-gripper robotic cells, where identical parts are produced and these parts completely follow a similar sequence. The lower bound of cycle time for such dual-gripper robotic cells is obtained by finding the cycle time of all related robot move cycles, and subsequently optimal robot task sequence, which is a two-unit cycle, is determined.

Scheduling of two-machine robotic rework cells

This study focuses on the domain of a two-machine robotic cell scheduling problem under three inspection scenarios. We propose the first analytical method for minimizing the partial cycle time of cells with in-process and post-process inspection scenarios, and then we convert this cell into a multi-function robotic cell with in-line inspection scenario. For the first scenario, parts are inspected in one of the production machines using multiple sensors, while the inspection process is performed by an independent inspection machine for the second scenario. Alternatively, the inspection can be performed by a multi-function robot for the third scenario. A distinguishing characteristic of this robot is that it can perform inspection of the part in transit. However, the robot cannot complete the part transition and load it on the next destination machine if it identifies a fault in the part. The stochastic nature of the process prevents us from applying existing deterministic solution methods for corresponding scheduling problems. In the first stage, we present a heuristic method that converts a multiple-sensor inspection system into a single-sensor inspection system. The expected cycle times of two different cycles are derived based on a geometric distribution, and then the maximum expected throughput is pursued for in-process and post-process inspection sensors, respectively. In the second stage, we develop the inspection system into an in-line inspection system using a multi-function robot. Finally, we determine if it is technically feasible and profitable to replace the in-process (or post-process) inspection scenario with the in-line inspection scenario. We study the scheduling of a two-machine robotic cell with an inspection process.All partial cycle times are derived under three different inspection scenarios.The maximum expected throughput is pursued for each inspection scenario.A multiple-sensor inspection is converted into a single-sensor inspection.We determine which inspection scenario has the highest performance.

Cyclic scheduling in small-scale robotic cells served by a multi-function robot

The objective of this study is to maximize the production rate of a rotationally arranged robotic cell by finding an optimal move cycle for a multi-function robot (MFR). Using this class of industrial robots makes the cell much more sophisticated than classical one where robot is considered to be only capable of handling material in work cells. MFR is able not only to transfer the part between two adjacent processing stages but also to perform a special operation in transit. The cycle time formulas are developed for small-scale cells where a robot interacts with either two or three machines. Also, this paper presents a methodology for finding the optimality regions of all possible cycles. This analysis results in enhancing the managerial skill for evaluating the productivity improvements of MFRs in robotized workcells.

A framework for stochastic scheduling of two-machine robotic rework cells with in-process inspection system

Scheduling of two-machine robotic rework cells with in-process inspection scenario.Converting multiple-sensor systems into single-sensor systems.Deriving cycle times of two different cycles based on a geometric distribution.A mechanism of finding the maximum expected throughput for in-process inspection.Focusing on the domain of the problem for three various kinds of pickup scenarios. This study is focused on the domain of a two-machine robotic cell scheduling problem for three various kinds of pickup scenarios: free, interval, and no-wait pickup scenarios. Particularly, we propose the first analytical method for minimizing the partial cycle time of such a cell with a PC-based automatic inspection system to make the problem more realistic. It is assumed that parts must be inspected in one of the production machines, and this may result in a rework process. The stochastic nature of the rework process prevents us from applying existing deterministic solution methods for the scheduling problem. This study aims to develop a framework for an in-line inspection of identical parts using multiple contact/non-contact sensors. Initially, we convert a multiple-sensor inspection system into a single-sensor inspection system. Then, the expected sequence times of two different cycles are derived based on a geometric distribution, and finally the maximum expected throughput is pursued for each individual case with free pickup scenario. Results are also extended for the interval and no-wait pick up scenarios as two well-solved classes of the scheduling problem. The waiting time of the part at each machine after finishing its operation is bounded within a fixed time interval in cells with interval pickup scenario, whereas the part is processed from the input conveyor to the output conveyor without any interruption on machines in cells with no-wait pickup scenario. We show a simple approach for solving these two scenarios of the problem which are common in practice.

A cross-entropy method for optimising robotic automated storage and retrieval systems

In this paper, we consider a robotic automated storage and retrieval system (AS/RS) where a Cartesian robot picks and palletises items onto a mixed pallet for any order. This robotic AS/RS not only retrieves orders in an optimal sequence, but also creates an optimal store ready pallet of any order. Adapting the Travelling Salesman Problem to warehousing, the decision to be made includes finding the optimal sequence of orders, and optimal sequence of items inside each order, that jointly minimise total travel times. In the first phase, as a control problem, we develop an avoidance strategy for the robot (or automatic stacker crane) movement sequence. This approach detects the collision occurrence causing unsafe handling of hazardous items and prevents the occurrence of it by a collision-free robot movement sequence. Due to the complexity of the problem, the second phase is attacked by a Cross-Entropy (CE) method. To evaluate the performance of the CE method, a computational analysis is performed over various test problems. The results obtained from the CE method are compared to those of the optimal solutions obtained using CPLEX. The results indicate high performance of the solution procedure to solve the sequencing problem of robotic AS/RSs.

Increasing Throughput for a Class of Two-Machine Robotic Cells Served by a Multifunction Robot

The multifunction robotic cell scheduling problem has been recently studied in the literature. The main assumption in the pertaining literature is that a multifunction robot performs an operation on the part during any loaded move between two adjacent processing stages. For a two-machine cell, these stages are the input hopper, the first machine, the second machine and the output hopper. Consequently, the multifunction robot performs three operations with fixed processing times. In contrast, we assume a class of two-machine cells where none of the processing times of three operations are fixed. However, their summation is fixed and equivalent to the processing time of the unique operation. The processing mode of the unique operation performed by the multifunction robot is “stop resume.” Thus, regardless of the gap interrupts during operations by two machines, the robot continues performing the unique operation of the part when it is reloaded to the robot without any loss of time. The focus lies on

Cyclic production for robotic cells served by multi-function robots with resumable processing regime

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Resolution of deadlocks in a robotic cell scheduling problem with post-process inspection system: Avoidance and recovery scenarios

-unit cycles due to their popularity. It is proven one-unit cycles have better performance for the problem under study. The cycle time of one-unit cycles are obtained and optimality conditions are determined for different pickup criteria: free, interval, and no-wait.