The impact of external disturbances on the performance of a cellular manufacturing systems

In manufacturing systems, different types of disturbances influence system’s performance, cellular manufacturing has been proposed as an approach to cope with the uncertainty characteristic of customer driven markets. However, even cellular manufacturing systems are prone to the effects of varying demand patterns. In this study, the effects of some aspects related to demand variation such as the arrival of material, the variety of products and the variation in product mix are investigated to identify those system characteristics that -within the context of cellular manufacturing systems- represent an advantage in the presence of such disturbances. To do so, discrete event simulation is used to conduct the experimentation by modelling a cellular manufacturing system. Additionally, statistical design of experiment is employed to identify the factors contributing to higher system performance. The results show that, in spite of the demand related disturbance, machines with low set-up duration and highly skilled operators constitute the most important characteristics of an efficient manufacturing cell

A genetic algorithm approach to designing and modelling of a multi-functional fractal manufacturing layout

A dynamic and optimal shop floor design, modelling and implementation is key to achieving successful Fractal Manufacturing System (FrMS). To build adaptive and fault-tolerant fractal layout, attention is paid to issues of shop floor planning, function layout, determination of capacity level, cell composition planning and flow distances of products. A full fledged FrMS. layout is multi-functional and is capable of producing a variety of products with minimal reconfiguration. This paper is part and a progression of an on-going project whereby Genetic Algorithm (GA) is adopted to design and model a flexible and multi-functional FrMS floor layout. GA is used in the project for modeling and simulation. The design implementation is done using MATLAB. The result is a fault tolerant configuration that self-regulates and adapts to unpredictable changes in the manufacturing environment arising from lead time reduction pressure, inventories, product customization and other challenges of a dynamic and volatile operational environment

An information fractal for supply network inventory optimisation

This paper develops a new conceptual framework for an information fractal to optimise inventory across the supply network by identifying the optimum safety stock, inventory policy and cycle stock with the lowest logistics cost as well as out of stock prevention. The proposed framework consists of two levels: top and bottom level fractals. Fractals in the bottom level analyse demand, optimise safety stock and recommend an inventory policy. Then transmit output to the top level fractal to investigate the effect of different replenishment frequencies to determine the optimum cycle stock for each fractal in the bottom level by integrating the inventory holding costs and transportation costs to minimise the logistics cost. The proposed framework provides a systematic method through which practitioners are able to decide upon the demand analysis, safety and cycle stock optimisatio

Fuzzy analytical hierarchy process for the selection of maintenance policies within petroleum industry

The selection of the maintenance policies is considered to be a complex matter at the strategic level and a trade-off between the criteria that should be considered is required to achieve the optimum maintenance selection. The purpose of this study is to develop a Fuzzy-Analytic Hierarchy Process multi criteria decision making model for the selection of maintenance policies within the petroleum industry. The model enables practitioners to decompose the structure of the hierarchy which assists in identifying the main criteria, sub-criteria and alternatives that impact on the selection of maintenance activities. The proposed AHP model is validated and in addition a comparison between classic and fuzzy analytic hierarchy process is conducted in terms of different derivation methods. Moreover, a sensitivity analysis is performed to validate the response of each derivation method at different inconsistency ratio which proved that the proposed model can be considered as the most accurate presentation of the criteria, sub-criteria and alternatives that should be used to decide upon the strategic maintenance policies within petroleum industry

Introducing a unique inventory control framework for centralized VMI and JIT production

The purpose of this research is to develop a new Information Fractal Structure (IFS) framework to facilitate communication and collaboration between centralized Vendor-Managed- Inventory (VMI) and Just-In-Time production to optimize inventory and logistics cost throughout the supply network. The proposed framework is conceptually developed, validated and implemented using mathematical and simulation modelling. Experimental factorial design and statistical techniques (MANOVA) are used to generate and analyze the results. The results demonstrated that the application of the proposed IFS provided a new effective collaboration protocol between centralized VMI and core manufacturer. Furthermore, the IFS led to an increase in both collaboration and integration and improve the process of sharing information across the network, which has proven to be a problematic area for industrialists

Responsiveness optimisation in the fractal supply network

Responsiveness is one of the significant performance measures in today's market based on which organisations can measure their success in seizing markets opportunities within Fractal Supply Chain. This paper aims to present this fractal supply network and also proposes a new mathematical model through which replenishment; transportation, production and handling time can be optimised at different stages of the fractal supply network. Both the proposed Fractal Supply Network and the mathematical model are implemented and validated using Supply Chain GURU Software. Application of the proposed mathematical model has led to a reduction in the total replenishment time and enables practitioners to systematically decide upon the optimum replenishment time at different stage of the network

Development of Lean Six-Sigma conceptual implementation model for manufacturing organisations

Due to the importance of manufacturing management models in enhancing the process performance and obtaining continuous improvement, it is apparent that both Six-Sigma and Lean management are two continuous improvement methodologies for improving the operation process and achieving high quality performance. The purpose of this paper is to develop a conceptual Lean six-sigma implementation model (LSS-M) for manufacturing organisations in order to entrench the strategic thinking into long term planning. The paper explores the literature pertinent to the topic and the necessary tools to carry out this research, the study used survey questionnaires to gather practitioners and academic opinion aiming at validating the proposed integrated model, its suitability for manufacturing organisation and identifying the barriers for successful implementation. The results clearly demonstrate that the proposed model is valuable to practitioners and academics and can assist manufacturing organisations to achieve competitive advantage if embedded in their long term strategic thinking

Development of an information fractal to optimise inventory in the supply network

The aim of this research paper is to develop a new conceptual framework for an information fractal to optimise inventory including safety stock, cycle stock and prevent stock out at lowest logistics cost and further enhance integration within the network. The proposed framework consists of two levels; top and bottom level fractals. Fractals in the bottom level analyse demand, optimise safety stock and then transmit output to the top level fractal. Fractals in the top level investigate different replenishment frequencies to determine the optimum cycle stock for each fractal in the bottom level. The proposed conceptual framework and a hypothetical supply network are implemented and validated using mathematical modelling and Supply Chain GURU Simulation Software; in order to optimise inventory in the supply network during the demand test period. Experimental factorial design and statistical techniques (MANOVA) are used to generate and analyse the results

Pollution routing problem with time window and split delivery

In most classic vehicle routing problems, the main goal is to minimise the total travel time or distance while, the green vehicle routing problem, in addition to the stated objectives, also focuses on minimising fuel costs and greenhouse gas emissions, including carbon dioxide emissions. In this research, a new approach in Pollution Routing Problem (PRP) is proposed to minimise the CO2 emission by investigating vehicle weight fill level in length of each route. The PRP with a homogeneous fleet of vehicles, time windows, considering the possibility of split delivery and constraint of minimum shipment weight that must be on the vehicle in each route is investigated simultaneously. The mathematical model is developed and implemented using a simulated annealing algorithm which is programmed in MATLAB software. The generated results from all experiments demonstrated that the application of the proposed mathematical model led to the reduction in CO2 emission