657 research outputs found
The Waikato River Settlement and Natural Resource Management in New Zealand
This paper examines the Waikato River Agreement in Principle by considering the implications of accommodating cultural values in natural resource management for the Waikato River and New Zealand. Economics will continue to play an integral part in the management of the Waikato River and natural resources in New Zealand. The settlement provides an opportunity to rethink how to incorporate Maori knowledge, cultural and social relationships, and social, cultural, and economic wellbeing in an integrated, holistic, and coordinated approach.water, cultural values, natural resource economics, co-management, Community/Rural/Urban Development, Environmental Economics and Policy, Land Economics/Use, Political Economy,
Intensification of smallholder livestock production, is it sustainable?
This paper discusses sustainability perspectives of intensification of different types of smallholder livestock production. A main sustainability issue of intensification is its contribution to household incomes. Smallholder dairying substantially increases incomes, despite pressing technical sustainability issues. Trade-offs are that it is not an option for the really resource-poor households, and its impact on different environmental and societal sustainability issues. Intensification of small animal systems appears to have a low potential to substantially increase incomes. Livestock intensification strategies have to meet the environmental and societal demands
Discrete Event Simulation Modelling for Dynamic Decision Making in Biopharmaceutical Manufacturing
With the increase in demand for biopharmaceutical products, industries have realised the need to scale up their manufacturing from laboratory-based processes to financially viable production processes. In this context, biopharmaceutical manufacturers are increasingly using simulation-based approaches to gain transparency of their current production system and to assist with designing improved systems. This paper discusses the application of Discrete Event Simulation (DES) and its ability to model the various scenarios for dynamic decision making in biopharmaceutical manufacturing sector. This paper further illustrates a methodology used to develop a simulation model for a biopharmaceutical company, which is considering several capital investments to improve its manufacturing processes. A simulation model for a subset of manufacturing activities was developed that facilitated âwhat-ifâ scenario planning for a proposed process alternative. The simulation model of the proposed manufacturing process has shown significant improvement over the current process in terms of throughout time reduction, better resource utilisation, operating cost reduction, reduced bottlenecks etc. This visibility of the existing and proposed production system assisted the company in identifying the potential capital and efficiency gains from the investments therefore demonstrating that DES can be an effective tool for making more informed decisions. Furthermore, the paper also discusses the utilisation of DES models to develop a number of bespoke productivity improvement tools for the company
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A modular hybrid simulation framework for complex manufacturing system design
For complex manufacturing systems, the current hybrid Agent-Based Modelling and Discrete Event Simulation (ABMâDES) frameworks are limited to component and system levels of representation and present a degree of static complexity to study optimal resource planning. To address these limitations, a modular hybrid simulation framework for complex manufacturing system design is presented. A manufacturing system with highly regulated and manual handling processes, composed of multiple repeating modules, is considered. In this framework, the concept of modular hybrid ABMâDES technique is introduced to demonstrate a novel simulation method using a dynamic system of parallel multi-agent discrete events. In this context, to create a modular model, the stochastic finite dynamical system is extended to allow the description of discrete event states inside the agent for manufacturing repeating modules (meso level). Moreover, dynamic complexity regarding uncertain processing time and resources is considered. This framework guides the user step-by-step through the system design and modular hybrid model. A real case study in the cell and gene therapy industry is conducted to test the validity of the framework. The simulation results are compared against the data from the studied case; excellent agreement with 1.038% error margin is found in terms of the company performance. The optimal resource planning and the uncertainty of the processing time for manufacturing phases (exo level), in the presence of dynamic complexity is calculated
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