Abstract
1- Introduction
2- Materials and method
3- Application of modeling techniques for case study
4- Conclusions
References
Abstract
The Safety in Operation system represents the framework within which every technological process operates. Any technological parameter – production, quality, must be analyzed in terms of this system. Mathematical and/or empirical modeling, as the first stage in the determination of the technological processes optimum operation regimes, represents a “must” both in the phase of conception, but mainly in the operation analysis phase. From this standpoint, the introduction of the active optimization method based on scheduled experiment represents an efficient tool to relieve the extreme conditions and to get information for technological processes optimum management. The work is focused on the mathematical modeling of the production function for an assembly of 13 drawing frames from two Romanian units, in terms of maintainability and reliability parameters. After determining the polynomial that characterizes the model, the work investigates the optimization of non-linear multi-variable polynomial function, and explains the context of getting the extreme values within the multi-factorial space. The work defines in its structure the notions of the safety in operation system used in research, applies quantitative study on a system from textile spinning mill field (one notices reliable operation times, break-down times, number of failures and the production of the technical systems on a pre-established time horizon); it statistically validates and mathematically optimizes the results. The theoretical approach consists in an algorithm in a unitary software application that can be used as a tool in the decision problems appeared during the technological process.
Introduction
Determination of wanted production values in terms of an established system of Safety in Function (SF) represents still a desiderate for all the technological processes (Pedro Moreu De Leon et al., 2012), (Damjan Maletic et al., 2014). The SF system is characterized by 4 parameters: Maintainability (M), Reliability (R), Security (S) and Disponibility (D) (Stapelberg, 2009). Because the disponibility is a linear function of maintainability and reliability, and security is a qualitative parameter, the problem reduces to optimizing the production parameter as function of M and R (Rachid et al., 2010). (Hincheeranan & Rivepiboon, 2012), (Stoica, 2010) and (Huang & Lai, 2003) propose new tools for measuring maintainability of system in the design phase that is a “must” to improves the maintainability of the system before to produce it, methods to whose results I have reported. In this paper I have referred to some of the metrics proposed in (Barabadi A, et. al. 2011) and (Babu & Bharathi (2013) and the proposed methods was based on the techniques described in (Reussner, 2003), and (Crowe & Feinberg, 2001).