Comparison of three flow line layouts with unreliable machines and profit maximization

Abstract

Manufacturing system design is a complex challenge when a new factory is being built. Although some factories produce the same product, the layouts of the factories may be different. Manufacturing systems for automotive engines can be modelled with several types of queueing networks with finite buffers and unreliable machines. In this paper, three types of layout structures which are commonly used in automotive engine shops are compared with respect to maximizing profit that is determined by throughput and the investment cost of buffers. We assume that the service times are constant but inhomogeneous, and the time to failure and the time to repair are exponentially distributed. To solve this problem we used approximation methods which are based on aggregation and overlapping decomposition for computing performance measures, and a gradient search method for finding an optimal buffer allocation.

Assessment of shop floor layouts in the context of process plans with alternatives

“…A layout establishes the physical location of the transforming resources, i.e., the facilities, machines, equipment, operators, etc. (Silva & Rentes, 2012;Wang et al, 2015;Cheng Ying et al, 2016). In addition, it establishes how transformed resources (i.e., raw materials, materials, parts, etc.)…”

“…In addition, it establishes how transformed resources (i.e., raw materials, materials, parts, etc.) should flow along operations (Wang et al, 2015;Cheng Ying et al, 2016). According to Silva & Rentes (2012), the physical location has impacts in several aspects on the shop floor, and Khilwani et al (2011) point out that the type of layout should focus on the flow of materials, seeking to increase production efficiency and reduce costs.…”

Optimisation of Buffer Allocations in Manufacturing Systems: A Study on Intra and Outbound Logistics Systems Using Finite Queueing Networks

“…G. Wang et al [57] compared three layout structures in automotive engine shops to maximise profit based on throughput and buffer investment costs. The analysis utilises queueing network models with finite buffers and unreliable machines, considering heterogeneous service times and exponentially distributed failure and repair times.…”

Ergonomics study and analysis of workstations in Tunisian mechanical manufacturing

“…5.4.1 Improving the implantation of machines, workstation, and work methodology Figure 9 shows an overview of the digital factory in its new configuration. This is an optimized configuration based on the flowchart of the gradient method research developed by Wang, Shin, and Moon (2016). Furthermore, the work areas were clearly marked and identified (zoning) with antifatigue mats in front of each machine to reduce fatigue caused by long periods of standing.…”