Microparticle surface layering through dry coating:impact of moisture content and process parameters on the properties of orally disintegrating tablets

OBJECTIVES: The aim of this study was to investigate the influence of process parameters during dry coating on particle and dosage form properties upon varying the surface adsorbed moisture of microcrystalline cellulose (MCC), a model filler/binder for orally disintegrating tablets (ODTs). METHODS: The moisture content of MCC was optimised using the spray water method and analysed using thermogravimetric analysis. Microproperty/macroproperty assessment was investigated using atomic force microscopy, nano-indentation, scanning electron microscopy, tablet hardness and disintegration testing. KEY FINDINGS: The results showed that MCC demonstrated its best flowability at a moisture content of 11.2% w/w when compared to control, comprising of 3.9% w/w moisture. The use of the composite powder coating process (without air) resulted in up to 80% increase in tablet hardness, when compared to the control. The study also demonstrated that surface adsorbed moisture can be displaced upon addition of excipients during dry processing circumventing the need for particle drying before tabletting. CONCLUSIONS: It was concluded that MCC with a moisture content of 11% w/w provides a good balance between powder flowability and favourable ODT characteristics.

Non-invasive winding fault detection for induction machines based on stray flux magnetic sensors

Non-intrusive monitoring of health state of induction machines within industrial process and harsh environments poses a technical challenge. In the field, winding failures are a major fault accounting for over 45% of total machine failures. In the literature, many condition monitoring techniques based on different failure mechanisms and fault indicators have been developed where the machine current signature analysis (MCSA) is a very popular and effective method at this stage. However, it is extremely difficult to distinguish different types of failures and hard to obtain local information if a non-intrusive method is adopted. Typically, some sensors need to be installed inside the machines for collecting key information, which leads to disruption to the machine operation and additional costs. This paper presents a new non-invasive monitoring method based on GMRs to measure stray flux leaked from the machines. It is focused on the influence of potential winding failures on the stray magnetic flux in induction machines. Finite element analysis and experimental tests on a 1.5-kW machine are presented to validate the proposed method. With time-frequency spectrogram analysis, it is proven to be effective to detect several winding faults by referencing stray flux information. The novelty lies in the implement of GMR sensing and analysis of machine faults.