Healthcare system must be sensitive to the needs of patient, financially viable and cost-effective. Emergency Department (ED) crowding and rising healthcare costs are perceived as significant issues that are getting worse. In order to respond to the growing number of incoming patients, hospital departments, including emergency rooms, have to re-evaluate their current facilities, procedures and practises from an operations management perspective. In a typical ED, it is important to minimise not only the patient's waiting time but also the staff idle time while maintaining the high utilisation rate of medical facilities. Computer simulation is recognised as a powerful tool, for medical management, to enquire productivity trying to increase service level to patients. Based on the analogy of a Job Shop Scheduling Problem (JSSP) and known patient scheduling methodologies, a metaheuristic Swarm Intelligence (SI) approach, focused on Ant System (AS) behaviour, was used in the balancing of an ED. The Ant Colony Optimisation (ACO) algorithm was implemented with the proposal to optimise patient scheduling under defined precedence, zoning and capacity constraints while balancing the workload between and within resource types. The ED of Cork University Hospital (CUH), Ireland, is the case in issue.

The plasma based Radica disinfection system reduces mattress bacterial colonization levels as compared to routine cleaning. This is a potentially important technology in the health care system to reduce surface colonisation and hence nosocomial infections.

This paper describes the development and early use of a test bed for Just‐In‐Time GIT) control of Flexible Assembly Systems (FAS). JIT has, up to now, been used in repetitive manufacturing systems. However, increasingly, companies involved in batch production who frequently use Materials Requirements Planning (MRP) approaches, are seeking to achieve the benefits of JIT, and to use Kanban type control at the operational level. The test bed simulation can be configured by the user to model a range of assembly systems each of which can, within limits, be configured by the experimenter. It is built using the SLAM II simulation package. Kanban cards are modelled as resources, as are the individual assembly stations and the transportation devices which carry work between the assembly stations. The test bed can be used to experiment with batch sizes, set‐up times, assembly station breakdowns, various Kanban sequences, varying purchasing lead times, etc. It allows experimentation with the application of the Kanban system to manufacturing systems which are not purely repetitive in nature and more closely resemble batch manufacturing systems.

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