Two-Machine Robotic Cell Sequencing under Different Uncertainties

Vaisi, Bahareh; Farughi, Hiwa; Raissi, S.

doi:10.2507/ijsimm17(2)434

Cited by 8 publications

(5 citation statements)

References 32 publications

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“…The typical automatic manufacturing systems are suitable mainly for mass production. Therefore, the uncertainty of system components can play an important role, but during the early stages of conceptual design, the ability to predict reliability is very limited [27,28].…”

Section: Introductionmentioning

confidence: 99%

Efficiency Analysis of Manufacturing Line with Industrial Robots and Human Operators

2020

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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.

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Section: Introductionmentioning

confidence: 99%

Efficiency Analysis of Manufacturing Line with Industrial Robots and Human Operators

2020

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“…In Vaisi et al [21], an availability reliability model for a two-machine robotic cell was presented for different sources of uncertainty. They implemented this structure on a multi-state transmission system.…”

Section: Literature Reviewmentioning

confidence: 99%

A simulation approach on reliability assessment of complex system subject to stochastic degradation and random shock

Pourhassan¹,

Raissi²,

Hafezalkotob³

2020

Eksploatacja i Niezawodność – Maintenance and Reliability

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Article citation info: PourhAssAn Mr, rAissi s, hAfezAlkotob A. A simulation approach on reliability assessment of complex system subject to stochastic degradation and random shock. eksploatacja i niezawodnosc -Maintenance and reliability 2020; 22 (2): 370-379, http://dx.doi. org/10.17531/ein.2020.2.20. Mohammad reza PourhAssAn sadigh rAissi Ashkan hAfezAlkotobA simulAtion ApproAch on reliAbility Assessment of complex system subject to stochAstic degrAdAtion And rAndom shock metodA symulAcyjnA oceny niezAwodności złożonego systemu podlegAjącego procesom degrAdAcji stochAstycznej i nArAżonego nA obciążeniA losoweMany systems are affected by different random factors and stochastic processes, significantly complicating their reliability analysis. In general, the performance of complicated systems may gradually, suddenly, or continuously be downgraded over times from perfect functioning to breakdown states or may be affected by unexpected shocks. In the literature, analytic reliability assessment examined for especial cases is restricted to applying the Exponential, Gamma, compound Poisson, and Wiener degradation processes. Consideration of the effect of non-fatal soft shock makes such assessment more challenging which has remained a research gap for general degraded stochastic processes. Through the current article, for preventing complexity of analytic calculations, we have focused on applying a simulating approach for generalization. The proposed model embeds both the stochastic degradation process as well randomly occurred shocks for two states, multi-state, and continuous degradation. Here, the user can arbitrarily set the time to failure distribution, stochastic degradation, and time to occurrence shock density function as well its severity. In order to present the validity and applicability, two case studies in a sugar plant alongside an example derived from the literature are examined. In the first case study, the simulation overestimated the system reliability by less than 5%. Also, the comparison revealed no significant difference between the analytic and the simulation result in an example taken from an article. Finally, the reliability of a complicated crystallizer system embedding both degradation and soft shock occurrence was examined in a threecomponent standby system.

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“…Accepted that if machine's failure/repair rates are constant over time, one may consider that time to failure and repair time deploy from an exponential distribution, otherwise, an alternate distribution such as Weibull, Gamma, or other density functions might be addressed for their modelling. In addition to the first seven assumptions in [68], the basic assumptions for the current study are summarized as follows:…”

Section: Assumptionsmentioning

confidence: 99%

“…Two well-defined examples derived from previous works [33,68] are applied to examine the relevancy to simulation-based optimization approach.…”

Section: Different Parts Casementioning

confidence: 99%

Schedule-Allocate and Robust Sequencing in Three-Machine Robotic Cell under Breakdowns

Vaisi

Farughi

Raissi

2020

Mathematical Problems in Engineering

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The purpose of this paper is to model two problems comprising schedule-allocate (in case of producing identical parts) and sequencing of parts (in case of producing different parts). The first model is used for minimizing the cycle time and operational cost, and the second one for minimizing both the mean and standard deviation of the total production cost as well the cycle time, in an unreliable three-machine robotic cell which confronted with many uncertainty factors. In the current article, mathematical modelling and simulation-based optimization method have been presented to schedule-allocate similar parts and trace the optimal sequence of different parts. Several solution procedures, including epsilon-constraint method and multiobjective particle swarm optimization algorithm, for identical parts case and response surface methodology for different parts case are applied. The results derived from solving numerical examples revealed some advantages in terms of time to attain the optimal solution.

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Two-Machine Robotic Cell Sequencing under Different Uncertainties

Cited by 8 publications

References 32 publications

Efficiency Analysis of Manufacturing Line with Industrial Robots and Human Operators

Efficiency Analysis of Manufacturing Line with Industrial Robots and Human Operators

A simulation approach on reliability assessment of complex system subject to stochastic degradation and random shock

Schedule-Allocate and Robust Sequencing in Three-Machine Robotic Cell under Breakdowns

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