**Abstract**

The main objective of this chapter is to examine and determine the main factors that have driven inflation rate in Malawi since 2001, with a special focus on the period 2013–2019, during which inflation rate has continuously declined reaching 9% in 2019, from 36% in 2013. The chapter also tries to assess whether this decline will continue as per the performance of the underlying economic fundamentals both in the short- and the long-run. The study employs the autoregressive distributed lag (ARDL) model framework to examine the drivers of inflation both in the short- and the long-run using quarterly data, over the period of 2001–2019. The results reveal that reduction in headline inflation has mainly been driven by money supply growth, fiscal deficits, and output growth in the short-run, while only output has driven inflation decline in the long-run. The results also show that after floating exchange rate in 2012, inflation decline has mainly been driven by output growth despite inflationary pressures from the exchange rate and import prices. Model forecasts show that inflation may increase up to 19.4% by December 2020, if money supply growth, fiscal deficits, and exchange rate movements are not taken care of.

**Keywords:** monetary policy, ARDL, unit root, co-integration, forecasts


**5.1. Ionic-liquid based magnetorheological fluids**

Guerrero-Sánchez et al. (Guerrero-Sánchez et al., 2007) were pioneers in the preparation of IL-based MRFs. More specifically, they prepared several suspensions consisting of either micron- or nanosized magnetite particles dispersed in eight different ILs. The most stable MRF was obtained for a composition of 10 vol % of magnetite microparticles suspended in [BuMeIm][PF6]. As a matter of fact, this MRF only exhibited a sedimentation ratio of 0.95 after two months of preparation. Having prepared a highly stable IL-based MRF was important, but even more important was the fact that colloidal stability was achieved without the addition of any stabilizing agents. The enhancement of stability was attributed to the physical adsorption of the IL ions on magnetite surface (for which they had strong affinity) that gave rise to steric repulsion between the dispersed particles. In the same work, the rheological behaviour of the samples upon magnetic field application was also studied concluding that the MR effect of the IL-based MRFs was comparable to those obtained for conventional MRFs, and high enough for practical purposes.

In a different work, Guerrero-Sánchez et al. (Guerrero-Sánchez et al., 2009) also used ILbased MRFs to study the influence of temperature on their MR behaviour. Here, ILs allowed extending such study to a broader range of temperature than in the case of conventional MRFs, due to their thermal stability and low vapour pressure. Something similar was pointed out by Dodbiba et al. (Dodbiba et al., 2007) who also took advantage of the good performance of ILs at high temperature to study the rheological behaviour upon magnetic field application of a mixture of two types of carbonyl iron powders dispersed in an IL. Therefore, these works make evident that the preparation of IL-based MFs is important from the fundamental point of view too.

Our group has also studied IL-based MRFs, especially for what concerns their stability. With this aim, Gómez-Ramírez et al. (Gómez-Ramírez et al., 2011) prepared IL-based MRFs differing both in the disperse phase material (pure iron and silica-coated iron particles) and in the liquid carrier ([EtMeIm][EtOSO3] and ([EtMeIm][Et2OPO3]). Additionally, conventional MRFs with mineral oil as liquid carrier were also synthesized. The particle volume fraction of all the samples was kept as 10 vol %. The most stable MRF was obtained by the combination of silicacoated iron particles and [EtMeIm][Et2OPO3]; for example, the viscosity of such MRF for shear rates over 100 s-1 almost coincided with the theoretical prediction of Batchelor equation, what means that only two-body hydrodynamic interactions existed between the particles, and, therefore, almost no magnetic aggregates were present. In fact, microscopic observations of the suspensions upon magnetic field application showed that field-induced particle chains had a more regular structure in the case of the most stable MRF (see figure 7). The worst results were obtained for mineral oil-based MRFs in which the particles were strongly aggregated and the resulting structures became more irregular. An intermediate behaviour was found for the suspensions with [EtMeIm][EtOSO3] as liquid carrier.

**Figure 7.** Field-induced particle structures in MRFs consisting of silica-coated iron microparticles dispersed in [EtMeIm][Et2OPO3] (a) and mineral oil (b). Bar length: 200 μm.

The improvement of MRF stability when using ILs as carriers, with respect to the ones prepared in mineral oil, was also explained by the adsorption of the IL ions on the surface of the dispersed particles. In a first approximation, such stability appears to be related to the electric conductivity of ILs, which, on its part, is also connected to the anion volume, being the first lower when the latter increases. Accordingly, if the adsorbed ions are larger, the steric repulsion between the particles is stronger too, leading to a decrease in particle aggregation. This is the reason for which a low conductivity-IL like [EtMeIm][Et2OPO3] gave rise to better results than the high conductivity-one [EtMeIm][EtOSO3]. The explanation for the higher stability in the case of MRFs consisting of silica-coated iron particles was the interaction between silica and the constituent IL ions. In fact, the wettability of both ILs was better in the case of silica-coated iron than for bare iron (Gómez-Ramírez et al. 2011).

The direct consequence of the improved stability of IL-based MRFs is a simpler MRF formulation, since no stabilizing additives are needed. This makes easier their preparation at larger scale given that no additional mixing steps are needed, for example. Therefore, stable MRFs with adequate MR response that can be subjected to ultra-high vacuum or very high/low temperatures are obtained, just by using ILs as carrier fluids.


**6.3 Thermography**

In addition to the use of the supervision system provided by the 9 FLUKE software, a thermovision is used, as shown in the figure, for measurement in low

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*Maintenance Management with Application of Computational Intelligence Generating…*

or high voltage electrical systems, temperature variations caused by excess electric current in the furnace motor/generator 01 be with the hot spot and it will not be

In **Figure 21**, we can identify the anomalies likely to occur in the electric motor of generator 1 for all effects of temperature caused by excessive electric current. The heating screen of **Figure 22** indicates that the engine/generator 1 cannot be related for preloading under operating plants. Other motors and generators are in the normal comfort area (A) and can be classified for normal operation of the diffuse rule such as the motors and tuners 2, 3, 4, 5, 6, 7, 8, 9, and 10. 5 and 25 mark as normal operations without interruption and execution of restriction only for the motor/

*6.3.1. Fuzzy logic goes into the operating conditions of the equipment*

generator 1. Activate the excluded points in your electronic connection.

able to pre-dispatch cargo, **Figure 20**.

*Iron content in the lubricating oil. Source: Authors.*

*DOI: http://dx.doi.org/10.5772/intechopen.82795*

*Water content and lubricating oil. Source: Authors.*

*Copper content in the lubricating oil. Source: Authors.*

**Figure 17.**

**Figure 18.**

**Figure 19.**

**Figure 16.** *Measurement points in the vibration analysis. Source: Authors.*

*Maintenance Management with Application of Computational Intelligence Generating… DOI: http://dx.doi.org/10.5772/intechopen.82795*

**Figure 17.**

*Maintenance Management*

**6.1 Vibration analysis**

global value (**Figure 16**).

lubricating oil.

**6.3 Thermography**

**6.2 Analysis of water content in lubricating oil**

*6.2.1 Analysis of metal content in lubricating oil*

*Measurement points in the vibration analysis. Source: Authors.*

simulation.

**Figures 12–15** show the results of the inference rules from the 3D surface of the graph. In the blank, all the forms of execution are present that can exist within the

Equipment status control is performed based on a calculated global value for the vibration signal measured at critical points on the machine surface. Since this value is due to a response signal from the structure to the dynamic excitation of the equipment operation, it represents a measure of the amplitude level of its vibration signal. In the case of the application for predictive maintenance, the international technical standards, among them the ISO, define two criteria for adoption of a

The determination of the presence and content of water in the case study was carried out through the distillation by drag. The sample is subjected to heating for distillation under controlled conditions, thus verifying the water content in the

The graph shows the results of the analysis of water content, done periodically as predictive, showing normal levels, since the tolerable content is 0.3% (**Figure 17**).

The graph made by direct reading (iron and copper) ferrography, which was carried out based on the extraction of the magnetizable contaminant particles, is contained in the lubricant, through the action of a magnetic field (**Figures 18** and **19**).

In addition to the use of the supervision system provided by the 9 FLUKE software, a thermovision is used, as shown in the figure, for measurement in low

**6. Case study (fuzzy logic with predictive maintenance).**

**54**

**Figure 16.**

*Water content and lubricating oil. Source: Authors.*

**Figure 18.** *Copper content in the lubricating oil. Source: Authors.*

**Figure 19.** *Iron content in the lubricating oil. Source: Authors.*

or high voltage electrical systems, temperature variations caused by excess electric current in the furnace motor/generator 01 be with the hot spot and it will not be able to pre-dispatch cargo, **Figure 20**.

#### *6.3.1. Fuzzy logic goes into the operating conditions of the equipment*

In **Figure 21**, we can identify the anomalies likely to occur in the electric motor of generator 1 for all effects of temperature caused by excessive electric current. The heating screen of **Figure 22** indicates that the engine/generator 1 cannot be related for preloading under operating plants. Other motors and generators are in the normal comfort area (A) and can be classified for normal operation of the diffuse rule such as the motors and tuners 2, 3, 4, 5, 6, 7, 8, 9, and 10. 5 and 25 mark as normal operations without interruption and execution of restriction only for the motor/ generator 1. Activate the excluded points in your electronic connection.

#### **Figure 20.**

*Copper content in lubricating oil. Source: Authors.*

#### **Figure 21.**

*Copper content in the lubricating oil. Source: Authors.*

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*Maintenance Management with Application of Computational Intelligence Generating…*

In **Figure 21** the parameters for the location of the equipment, according to the engine/generator 1, are not allowed to operate because they are not in good operating condition. The other engines and generators are located in area A (N) normal 2, 3, 4, 5, 6, 7, 8, 9, and 10 and are able to position themselves according to the needs of the organization. **Figure 22** informs which engines are conditional ideal

The objective of this work was to analyze the maintenance management system and its optimization through nebulous logic for the development of an intelligent system of support and decision-making for an ideal load dispatch demand. The interface of the developed computational tool achieved the simplicity desired by the users themselves, as well as the ease of learning in their operation. According to the facts presented in this paper, it was possible to show that, currently, a predictive maintenance program and a total maintenance program are indispensable for large companies. This is to provide reliability to processes and equipment, detecting problems still in the initial phase. Programs of this type provide good maintenance planning for the maintenance industry. Thus, the company grows with regard to meeting deadlines, resulting in an increase in customer satisfaction. In the present study, the gains from the two plans mentioned above could be assessed based on the information from the case study; we verified the reduction of corrective maintenance, and we verified the results with the increase of the MTBF and the decrease of the MTTR. The observed case can be implemented in any power generation machine that uses the fuel oil and, consequently, the use of oil stock, independent of the tank capacity and storage tank scales, which have only the standards of this system. The case study presented here can be implemented in any thermoelectric plant, independent of the loads to be dispatched, since the variables

The authors gratefully acknowledge the support of this research by FAPEAM,

*DOI: http://dx.doi.org/10.5772/intechopen.82795*

**7. Results achieved**

of this system are common to all.

UFPA, ELETROBRAS, and ITEGAM.

**Acknowledgements**

for pre-shipment of cargo under operating conditions.

**Figure 22.**

*Copper content in the lubricating oil. Source: Authors.*

*Maintenance Management with Application of Computational Intelligence Generating… DOI: http://dx.doi.org/10.5772/intechopen.82795*

In **Figure 21** the parameters for the location of the equipment, according to the engine/generator 1, are not allowed to operate because they are not in good operating condition. The other engines and generators are located in area A (N) normal 2, 3, 4, 5, 6, 7, 8, 9, and 10 and are able to position themselves according to the needs of the organization. **Figure 22** informs which engines are conditional ideal for pre-shipment of cargo under operating conditions.