Efficiency Analysis of Manufacturing Line with Industrial Robots and Human Operators

Abstract

The problem of production flow and evaluation of productivity in the manufacturing line is analysed. Machines can be operated by humans or by robots. Since breakdowns and human factors affect the destabilization of the production processes, robots are preferred. The main problem is a proper methodology—how can we determine the real difference in work efficiency between human and robot at the design stage? Therefore, an analysis of the productivity and reliability of the machining line operated by human operators or industrial robots is presented. Some design variants and simulation models in FlexSim have been developed, taking into consideration the availability and reliability of the machines, operators and robots. Traditional productivity metrics, such as the throughput and utilization rate, are not very helpful for identifying the underlying problems and opportunities for productivity improvement in a manufacturing system, therefore we apply the OEE (overall equipment effectiveness) metric to present how the availability and reliability parameters influence the performance of the workstation, in the short and long terms. The implementation results of a real robotic line from industry are presented with the use of the overall factory efficiency (OFE) metric. The analysis may help factories achieve the level of world class manufacturing.

Integration and Evaluation of Intra-Logistics Processes in Flexible Production Systems Based on OEE Metrics, with the Use of Computer Modelling and Simulation of AGVs

“…The FMS has been studied over the last couple of decades and the researchers have found a variety of problems, which can be distributed in three major categories: workshop design, transportation network design and scheduling problems [31,32]. Different methods were used to solve them, including mathematical (linear, constraints, stochastic) programming, combinatorial optimization, Petri nets and scenario analysis, but computer simulation, especially Discrete Event Simulation (DES), is the most universal and widely used one [33], e.g., for the design of manufacturing systems [27], efficiency [9] and stability analysis [34] of production systems and the design of warehouse transportation systems with Automated Guided Vehicles (AGVs) [35][36][37].…”

“…Then the Discrete Event Simulation (DES) method was used for performing the series of experiments and an analysis of results is presented in form of Overall Factory Efficiency (OFE) and Overall Transport Efficiency (OTE). Our previous works [7][8][9] show that the computer simulation of the detailed model of the production line with machines, operators and robots with reliability parameters allows better representation and understanding of a real production process which is important for early design and enables front-end planning.…”

The Review of Reliability Factors Related to Industrial Robo

“…Robots are designed in such way that any single, reasonably foreseeable failure will not lead to the robot's hazardous motion [13].Modern industrial robots are designed to be universal manipulating machines, which can have different sort of tools and equipment for specific types of work. However, the robot's equipment is often custom made and may turn out to be unreliable as presented in, therefore, the whole robotic system requires periodic maintenance, following to the manufacturer's recommendations [14][15]. operators and robots in cooperative tasks, therefore, the safety plays a key role.…”

Modeling, Assessment and Design of an Emergency Department of a Public Hospital through Discrete-Event Simulation

“…The constant technological advancement has enhanced the development of simulation software that is increasingly robust and capable of numerically translating a real scenario. This fact made it possible to test changes to existing processes without the need to implement them on a real scale [17,18]. Despite representing a theme that has been cherished in academia since 1950, its use as a tool to analyse issues related to production only proliferated from 1986 onwards [19].…”