Quantifying the Impact of Layout on Productivity: An Analysis from Robotic-Cell Manufacturing

Abstract

Although the impact of layout on the productivity of manufacturing systems is well recognized, a quantification of this impact is an issue that is often ignored or crudely approximated in practice. When evaluating competing layouts for a manufacturing system, the trade-off between their relative benefits and their relative costs underlines the need for a reasonably accurate comparison of the productivity offered by these potential layouts. In this paper, we argue for this approach by comparing the productivity of two well-known layouts in robotic-cell manufacturing: circular and linear. We consider the problem of optimizing throughput in single-gripper, bufferless robotic cells that produce identical parts under the free-pickup criterion and the additive-travel-time metric. For cells with a circular layout, we show that the problem of finding an optimal 1-unit cycle is NP-hard. Our main algorithmic result is a polynomial-time 5/3-approximation algorithm for this problem. We then demonstrate that our algorithm provides near-optimal solutions by compiling its performance on an extensive test bed of practically-relevant instances. Finally, we use the algorithm to assess the increase in throughput for cells with a circular layout over those with a linear layout. We show that a circular layout offers a significant improvement in productivity and demonstrate the robustness of this improvement by examining the sensitivity with respect to changes in the design parameters of the robotic cell. Thus, our work provides operations managers with a tool to trade off the resulting increase in revenue with the additional cost of acquiring and maintaining a robot that can exploit a circular layout.

Approximations to optimal sequences in single-gripper and dual-gripper robotic cells with circular layouts

“…1(a) travels from the output buffer O to machine M 1 by moving counterclockwise (passing I, time 2δ) because clockwise travel (traversing machines M 5 , M 4 , M 3 , and M 2 , time 5δ) would require more time. This flexibility in robot movements can significantly improve the productivity of a cell; however, the sequencing of operations becomes more challenging, even for single-gripper cells (Brumson, 2001;Rajapakshe et al, 2011). Furthermore, schedules that are optimal in linear cells are not necessarily optimal in circular cells (Geismar, Sethi, Sidney, and Sriskandarajah, 2005), so different techniques are required to find efficient robot sequences.…”

Challenges and key technologies in robotic cell layout design and optimization

“…The empirical design often seems to buy a lottery on the final cell productivity via its respective cost-benefit analysis. 9 Over the years, many previous studies trying to give a problem-solving answer have taken some steps forward in this area. Mata and Tubaileh discuss the workstation layout problem in manufacturing cell served by a single robot.…”

Scheduling robotic cells served by a dual-arm robot

“…In contrast, Akturk et al (2005) studied flexible cells using a linear cell layout. Rajapakshe et al (2011) showed that the problem RF 1;1 m• |free,A,cyclic-1|C t is NP-hard. Our current article analyzes circular cells with dual-arm robots by examining all possible sequences, calculating their respective throughputs under this travel time metric, and determining the specific circumstances under which each is optimal.…”

“…This is common in the literature. Examples include Sethi et al (1992), Lei and Wang (1994), Crama and Van de Klundert (1997), Hall et al (1997), Levner et al (1997), Venkatesh et al (1997), Agnetis (2000), Herrmann et al (2000), Brauner and Finke (2001), Che et al (2003), , Akturk et al (2005), Kumar et al (2005), Dawande et al (2010), and Rajapakshe et al (2011). Thus, any part in the cell is always either on one of the machines or being handled by one of the two robot arms.…”