Browsing by Author "Sachidananda, Madhu"

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    A concept of water usage efficiency to support water reduction in manufacturing industry
    (MDPI, 2016-11-25) Sachidananda, Madhu; Webb, D. Patrick; Rahimifard, Shahin
    Increasing pressures on freshwater supplies, continuity of supply uncertainties, and costs linked to legislative compliance, such as for wastewater treatment, are driving water use reduction up the agenda of manufacturing businesses. A survey is presented of current analysis methods and tools generally available to industry to analyze environmental impact of, and to manage, water use. These include life cycle analysis, water footprinting, strategic planning, water auditing, and process integration. It is identified that the methods surveyed do not provide insight into the operational requirements from individual process steps for water, instead taking such requirements as a given. We argue that such understanding is required for a proactive approach to long-term water usage reduction, in which sustainability is taken into account at the design stage for both process and product. As a first step to achieving this, we propose a concept of water usage efficiency which can be used to evaluate current and proposed processes and products. Three measures of efficiency are defined, supported by a framework of a detailed categorization and representation of water flows within a production system. The calculation of the efficiency measures is illustrated using the example of a tomato sauce production line. Finally, the elements required to create a useable tool based on the efficiency measures are discussed.
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    Conceptualising the impact of information asymmetry on through-life cost: case study of machine tools sector
    (Elsevier, 2019-11-02) Farsi, Maryam; Grenyer, Alex; Sachidananda, Madhu; Sceral, Mario; Mcvey, Steve; Erkoyuncu, John Ahmet; Roy, Rajkumar
    Information asymmetry (IA) in terms of contextual variety and importance is one of the most challenging aspects of through-life costing in product-service systems (PSS). IA is an imbalance in the information, data and knowledge shared among the parties involved in a contractual agreement. In manufacturing systems under PSS, interaction and effective communication among several parties who are involved in a contractual agreement, rely on the continuity and accuracy of information and context. In such systems, contextual variety exhibits complexity and uncertainty in through-life costing and subsequently in PSS cost assessment. Although the economic aspect of PSS has been studied previously, the impact of IA on through-life cost and for different PSS solutions has not been detailed. Considering manufacturing value chains, this paper introduces a new concept of PSS-hierarchy to perform through-life costing in the presence of IA for various PSS solutions. Moreover, this paper proposes a generic life-cycle model for different PSS solutions to assess the total cost of ownership (TCO). The proposed model has been developed to support decisions on contract design in manufacturing systems. This study considers the manufacturer, service provider and customer perspectives to develop the TCO model using a machine tool manufacturing case study.
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    Discrete Event Simulation Modelling for Dynamic Decision Making in Biopharmaceutical Manufacturing
    (Elsevier, 2016-07-28) Sachidananda, Madhu; Erkoyuncu, John Ahmet; Steenstra, Daniel; Michalska, Sandra
    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 ‘what-if’ 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.