New composite polyvinyl alcohol (PVA)/polypropylene (PP) membranes were prepared by combining both solution electrospinning and melt electrospinning methods. Self‐designed and made needleless melt electrospinning device was used to fabricate PP membranes which acted as the support layer. PVA membrane on the surface was fabricated via solution electrospinning. The electrospun PVA/PP composite membranes were characterized by the pore size distribution, pure water flux, and rejection ratio, then compared with general composite membranes. Characterizations revealed that the fiber diameter of solution electrospun PVA membrane and melt electrospun PP membrane were 0.171 ± 0.027 and 2.24 ± 0.33 μm, respectively, and the average pore size was 0.832 μm and 27.29 μm, which was much smaller than the nonwoven membrane. The rejection ratio to the 500 nm particles of the PVA/PP …

Melt electrospinning, a technique that has gained increasing attention since it easily can generate continuous ultrafine fibers directly from polymer melts without the use of any solvent. Therefore, it is considered as a safe, cost effective, and environmental friendly technique. However, with all those great advantages, the technique still suffers some drawbacks such as: large fiber diameter and low throughput. The hot air assisted melt differential electrospinning (MDES) is a new technique invented by our research team that can solve or eliminate those drawbacks. The most important features of our used apparatus are: Needleless nozzle that could generate multiple Taylor cones around the bottom edge of the nozzle, which can result in a high throughput. The stretching force acting on the jets can be further strengthened by an air current provided by an air pressure gun. Interference between the high voltage supply …

Solventless melt electrospinning which allows mass production is substantially safe. It can produce fibres of hundreds of nanometres, one order of magnitude lower than that of conventional melt-blown spinning. In this paper, a comparison between different technologies producing ultra-fine fibre reveals the advancement of melt electrospinning method using umbellate spinneret for ultra-fine fibre mass production. Some typical industrial polymer materials was also spun using melt electrospinng method, including biodegradable materials like polylactic acid and polycaprolactone (PCL), which may contribute to some interesting applications. In addition, a machine for mass production is also proposed. Finally, proposition of the industrialisation of ultra-fine fibre by melt electrospinning is discussed.

Ultrafine polypropylene (PP) fibers as oil sorbents were fabricated via a needleless melt‐electrospinning device and were characterized by scanning electron microscopy and contact‐angle analysis. PP fibers of various diameters and porosities were obtained by the manipulation of the applied electrical field. The effects of the fiber diameter and porosity on the oil‐sorption capacity and oil‐retention behavior were investigated. The experimental results demonstrate that for fiber diameter on the microscale, the porosity played a paramount role in determining the oil‐sorption capacities. The maximum oil‐sorption capacity of the resulting PP fibers with regard to motor oil and peanut oil were 129 and 80 g/g, respectively; these values were approximately six to seven times that of commercial PP nonwoven fabricated through the melt‐blown method. In addition, even after seven sorption/desorption cycles, the oil‐sorption …

This paper demonstrates a new approach in solving problems with capacity issues within a cement factory in Libya using the Witness simulation package that enables the development of discrete and continuous simulation model to simulate these processes. The model aims to support the implementation of management systems in Supply Chain Management and the introduction of Just-In-Time systems. In order to carry out the above, research has been carried out into processes of SCM and J.I.T. The developed Simulation model is based on Libyan Cement industry, exploring supply chain management (SCM) and Just IN Time (JIT) system from start to end of the processes. Therefore, the aim and objective of investigating supply chain management and applying JIT to the cement factory using simulation at the very stage has been successful and has exercised with the simulation scenarios 1,2 and 3. This was achievable simply based on many assumptions as addressed above and with the help of the witness software that executes duties with the aid of input and output rules that need to be applied accordingly.

Toyota, in Japan started the creation of this method in the early 1960's and hence it is also known as the “Toyota Production System” as it was used for their production of their automobiles. Therefore, the best definition of this system comes from Toyota i.e. JIT is a disciplined programme for improving overall productivity and reducing waste. It provides for the cost-effective production and delivery of only the necessary required parts, in the right quantity, at the right time and place, while using a minimum amount of facilities, equipment, materials and human resources. JIT is dependent upon the balance between the supplier's flexibility and user's stability. It is accomplished through the application of specific techniques that require total employee involvement and teamwork.

This paper considers a common problem that all industries contest with in practice ie the breaking down of machines that influence production and cost directly. In a majority of industrial applications, acquiring optimum utilisation of all available resources for existing and future predicted demand is a major function throughout all the levels of management. This paper uses a number of analytical tools and software that support one another ie Witness Simulation, Bayesian Network Modelling and Hugin Software. The use of expert experience and knowledge has been incorporated throughout the study as it is vital to model building and greater understanding of machine breakdown. This study uses discrete event simulation and Bayesian network modelling collectively to understand machine breakdowns to increase efficiency within a cement manufacturing plant ie the Crusher Machine. The Bayesian network modelling implemented by the Hugin Software is used to generate probabilities which are transferred into a discrete event simulation model using Witness Software based on the historical data, expert knowledge and opinions. The model simulates the three parameters of the machine life based on consumption of each parameter. This is translated into a probability failure rate that changes as the model is running. The model demonstrates decisions based on the probability of failure from the Bayesian model and based on life consumption of the different variables in the simulation model.

This paper looks into how simulation can be used and developed to combat and aid integrated maintenance and cost optimisation of Libyan cement factory by using simulation as an intelligent maintenance tool to enable intelligent decisions to be made by maintenance management. The cost of preventive maintenance against corrective maintenance, the loss of production and the delay in schedule. Also this paper presents a methodology by integrating maintenance, repair and replacement decisions in bridge management based on reliability, optimization, and life-cycle cost. The overall total cost incurred per minute due to machine failure for more intelligent maintenance decision making. The end result of the model identifies a true to life cost of preventive and corrective maintenance incurred by organisation due to failures.

This paper presents a new approach using Witness Simulation in combating issues related to maintenance within the existing manufacturing facility. Currently, maintenance is a key issue as many machines breakdown due to every day wear and tear as well as the age of the machine itself. This causes bottlenecks within the entire production system as the schedules of production is disturbed and further backlogs are developed. Also, when machines breakdown there seems to be very little communication from one end to another ie parts are needed for the repair of many of the machines, for example, it is very common for the rotary kiln to come to a halt due to increased temperature and different quantities of a mixture of materials. In order to fix the problem and move back on schedule the maintenance team uses certain materials ie same materials, all the time. However, due to not having an adequate stock control system and the lack of communication many a times, parts are not readily available and hence the team wait further until parts arrive at the facility. This paper will demonstrate how all of the above problem areas can be adhered to via the use of adopting a simple automated response system using Witness Simulation. The demonstration will be based on a single machine for testing purposes to ensure efficiency that can later be applied to the entire system as a whole.

This paper explores the use of Bayesian network modeling of machine breakdowns within a cement manufacturing plant. The Bayesian network modeling is introduced using Hugin software and then implemented into a Witness Simulation model using historical data, expert knowledge and opinions. The models simulate 3 parameters of the machine based on life consumption and usage of each parameter, the developed Witness model produces a probability failure rate based on these parameter usages. The failure probability developed by Witness is implemented using the Chain Rule; this is compared with the probability for failure based on the Bayesian network model. This enables the user to see the probability of failure developed by the implementation of the chain rule and Witness based on the parameter usage, on a live streaming fashion as the model is running. This can be used as a decision making tool for management to consider machine maintenance affectively based on parameter usage.