Desenvolvimento de um sistema para planeamento e controlo da produção

Atualmente o sector industrial está inserido num mercado cada vez mais competitivo, onde é exigida uma estratégia empresarial que possa garantir a sua permanência e destaque no atual mercado. Por esta razão, um planeamento e controlo da produção adequado torna-se essencial para o bom funcionamento de uma empresa. Através destes sistemas é possível atuar de forma positiva na produção, rentabilizando-se o sector produtivo da empresa que contribui para o aumento da qualidade de serviço e também para o crescimento económico da empresa. Com um planeamento da produção adequado, uma organização dispondo das mesmas capacidades, é capaz de produzir quantidades iguais num menor intervalo de tempo. Por outro lado, um controlo da produção preciso é imprescindível para o fornecimento da informação correta quando necessária. No sentido de otimização, uma empresa apresentou algumas sugestões de melhoria a nível do planeamento e controlo da produção. Este trabalho surge assim com o intuito de dar resposta às propostas apresentadas. Para tal, no desenvolvimento desta dissertação, criou-se uma ferramenta dotada de dois algoritmos e um sistema de controlo para aquisição de informação de forma automatizada. Em suma, o sistema proposto apresenta a capacidade de construção de boas soluções para o planeamento, conciliada com um sistema de aquisição de dados bastante prático e e caz. Mantendo sempre a exibilidade necessária para um sistema deste género.

Path planning, guidance and control for a UAV forced landing

A forced landing is an unscheduled event in flight requiring an emergency landing, and is most commonly attributed to engine failure, failure of avionics or adverse weather. Since the ability to conduct a successful forced landing is the primary indicator for safety in the aviation industry, automating this capability for unmanned aerial vehicles (UAVs) will help facilitate their integration into, and subsequent routine operations over civilian airspace. Currently, there is no commercial system available to perform this task; however, a team at the Australian Research Centre for Aerospace Automation (ARCAA) is working towards developing such an automated forced landing system. This system, codenamed Flight Guardian, will operate onboard the aircraft and use machine vision for site identification, artificial intelligence for data assessment and evaluation, and path planning, guidance and control techniques to actualize the landing. This thesis focuses on research specific to the third category, and presents the design, testing and evaluation of a Trajectory Generation and Guidance System (TGGS) that navigates the aircraft to land at a chosen site, following an engine failure. Firstly, two algorithms are developed that adapts manned aircraft forced landing techniques to suit the UAV planning problem. Algorithm 1 allows the UAV to select a route (from a library) based on a fixed glide range and the ambient wind conditions, while Algorithm 2 uses a series of adjustable waypoints to cater for changing winds. A comparison of both algorithms in over 200 simulated forced landings found that using Algorithm 2, twice as many landings were within the designated area, with an average lateral miss distance of 200 m at the aimpoint. These results present a baseline for further refinements to the planning algorithms. A significant contribution is seen in the design of the 3-D Dubins Curves planning algorithm, which extends the elementary concepts underlying 2-D Dubins paths to account for powerless flight in three dimensions. This has also resulted in the development of new methods in testing for path traversability, in losing excess altitude, and in the actual path formation to ensure aircraft stability. Simulations using this algorithm have demonstrated lateral and vertical miss distances of under 20 m at the approach point, in wind speeds of up to 9 m/s. This is greater than a tenfold improvement on Algorithm 2 and emulates the performance of manned, powered aircraft. The lateral guidance algorithm originally developed by Park, Deyst, and How (2007) is enhanced to include wind information in the guidance logic. A simple assumption is also made that reduces the complexity of the algorithm in following a circular path, yet without sacrificing performance. Finally, a specific method of supplying the correct turning direction is also used. Simulations have shown that this new algorithm, named the Enhanced Nonlinear Guidance (ENG) algorithm, performs much better in changing winds, with cross-track errors at the approach point within 2 m, compared to over 10 m using Park's algorithm. A fourth contribution is made in designing the Flight Path Following Guidance (FPFG) algorithm, which uses path angle calculations and the MacCready theory to determine the optimal speed to fly in winds. This algorithm also uses proportional integral- derivative (PID) gain schedules to finely tune the tracking accuracies, and has demonstrated in simulation vertical miss distances of under 2 m in changing winds. A fifth contribution is made in designing the Modified Proportional Navigation (MPN) algorithm, which uses principles from proportional navigation and the ENG algorithm, as well as methods specifically its own, to calculate the required pitch to fly. This algorithm is robust to wind changes, and is easily adaptable to any aircraft type. Tracking accuracies obtained with this algorithm are also comparable to those obtained using the FPFG algorithm. For all three preceding guidance algorithms, a novel method utilising the geometric and time relationship between aircraft and path is also employed to ensure that the aircraft is still able to track the desired path to completion in strong winds, while remaining stabilised. Finally, a derived contribution is made in modifying the 3-D Dubins Curves algorithm to suit helicopter flight dynamics. This modification allows a helicopter to autonomously track both stationary and moving targets in flight, and is highly advantageous for applications such as traffic surveillance, police pursuit, security or payload delivery. Each of these achievements serves to enhance the on-board autonomy and safety of a UAV, which in turn will help facilitate the integration of UAVs into civilian airspace for a wider appreciation of the good that they can provide. The automated UAV forced landing planning and guidance strategies presented in this thesis will allow the progression of this technology from the design and developmental stages, through to a prototype system that can demonstrate its effectiveness to the UAV research and operations community.

Motion planning and stochastic control with experimental validation on a planetary rover

Motion planning for planetary rovers must consider control uncertainty in order to maintain the safety of the platform during navigation. Modelling such control uncertainty is difficult due to the complex interaction between the platform and its environment. In this paper, we propose a motion planning approach whereby the outcome of control actions is learned from experience and represented statistically using a Gaussian process regression model. This model is used to construct a control policy for navigation to a goal region in a terrain map built using an on-board RGB-D camera. The terrain includes flat ground, small rocks, and non-traversable rocks. We report the results of 200 simulated and 35 experimental trials that validate the approach and demonstrate the value of considering control uncertainty in maintaining platform safety.

Contamination routes and control of Listeria monocytogenes in Food Production

Listeria monocytogenes is the causative agent of the severe foodborne infection listeriosis. The number of listeriosis cases in recent years has increased in many European countries, including Finland. Contamination of the pathogen needs to be minimized and growth to high numbers in foods prevented in order to reduce the incidence of human cases. The aim of this study was to evaluate contamination routes of L. monocytogenes in the food chain and to investigate methods for control of the pathogen in food processing. L. monocytogenes was commonly found in wild birds, the pig production chain and in pork production plants. It was found most frequently in birds feeding at landfill site, organic farms, tonsil samples, and sites associated with brining. L. monococytogenes in birds, farms, food processing plant or foods did not form distinct genetic groups, but populations overlapped. The majority of genotypes recovered from birds were also detected in foods, food processing environments and other animal species and birds may disseminate L. monocytogenes into food chain. Similar genotypes were found in different pigs on the same farm, as well as in pigs on farms and later in the slaughterhouse. L. monocytogenes contamination spreads at farm level and may be a contamination source into slaughterhouses and further into meat. Incoming raw pork in the processing plant was frequently contaminated with L. monocytogenes and genotypes in raw meat were also found in processing environment and in RTE products. Thus, raw material seems to be a considerable source of contamination into processing facilities. In the pork processing plant, the prevalence of L. monocytogenes increased in the brining area, showing that the brining was an important contamination site. Recovery of the inoculated L. monocytogenes strains showed that there were strain-specific differences in the ability to survive in lettuce and dry sausage. The ability of some L. monocytogenes strains to survive well in food production raises a challenge for industry, because these strains can be especially difficult to remove from the products and raises a need to use an appropriate hurdle concept to control most resistant strains. Control of L. monocytogenes can be implemented throughout the food chain. Farm-specific factors affected the prevalence of L. monocytogenes and good farm-level practices can therefore be utilized to reduce the prevalence of this pathogen on the farm and possibly further in the food chain. Well separated areas in a pork production plant had low prevalences of L. monocytogenes, thus showing that compartmentalization controls the pathogen in the processing line. The food processing plant, especially the brining area, should be subjected to disassembling, extensive cleaning and disinfection to eliminate persistent contamination by L. monocytogenes, and replacing brining with dry-salting should be considered. All of the evaluated washing solutions decreased the populations of L. monocytogenes on precut lettuce, but did not eliminate the pathogen. Thus, the safety of fresh-cut produce cannot rely on washing with disinfectants, and high-quality raw material and good manufacturing practices remain important. L. monocytogenes was detected in higher levels in sausages without the protective culture than in sausages with this protective strain, although numbers of L. monocytogenes by the end of the ripening decreased to the level of < 100 MPN/g in all sausages. Protective starter cultures provide an appealing hurdle in dry sausage processing and assist in the control of L. monocytogenes.

Production systems and supplier selection: a multi-phase process model

Purpose: This paper presents a combined multi-phase supplier selection model. The process repeatedly revisits the criteria and sourcing decision as the development process continues. This enables a structured adoption of product and production system innovation from strategic suppliers, where previously the literature purely focuses on product innovation or cost reduction. Design/methodology/approach: The authors adopted an embedded researcher style, inductive, qualitative case study of an industrial supply cluster comprising a focal automotive company and its interaction with three different strategic stamping suppliers. Findings: Our contribution is the multi-phased production and product innovation process. This is an advance from traditional supplier selection and also an extension of ideas of supplier-located product development as it includes production system development, and complements the literature on working with strategic suppliers. Specifically, we explicitly articulate the previously unreported issue of whether a supplier chosen for its innovation capabilities at the start of the new product development process will also be the most appropriate supplier during the production system development phase, when an ability to work collaboratively may be the most important attribute, or in the large-scale production phase when an ability to manufacture at low unit cost may be most important. Originality/value: The paper identifies a multi-phase approach to tendering within a fixed body of strategic suppliers which seeks to identify the optimum technological and process decisions as well as the traditional supplier sourcing choice. These areas have not been combined before and generate a valuable approach for firms to adopt as well as for researchers to extend our understanding of a highly complex process.

Understanding safety and production risks in rail engineering planning and protection

Much of the published human factors work on risk is to do with safety and within this is concerned with prediction and analysis of human error and with human reliability assessment. Less has been published on human factors contributions to understanding and managing project, business, engineering and other forms of risk and still less jointly assessing risk to do with broad issues of ‘safety’ and broad issues of ‘production’ or ‘performance’. This paper contains a general commentary on human factors and assessment of risk of various kinds, in the context of the aims of ergonomics and concerns about being too risk averse. The paper then describes a specific project, in rail engineering, where the notion of a human factors case has been employed to analyse engineering functions and related human factors issues. A human factors issues register for potential system disturbances has been developed, prior to a human factors risk assessment, which jointly covers safety and production (engineering delivery) concerns. The paper concludes with a commentary on the potential relevance of a resilience engineering perspective to understanding rail engineering systems risk. Design, planning and management of complex systems will increasingly have to address the issue of making trade-offs between safety and production, and ergonomics should be central to this. The paper addresses the relevant issues and does so in an under-published domain – rail systems engineering work.

A linear optimization approach to the combined production planning model

Two fundamental processes usually arise in the production planning of many industries. The first one consists of deciding how many final products of each type have to be produced in each period of a planning horizon, the well-known lot sizing problem. The other process consists of cutting raw materials in stock in order to produce smaller parts used in the assembly of final products, the well-studied cutting stock problem. In this paper the decision variables of these two problems are dependent of each other in order to obtain a global optimum solution. Setups that are typically present in lot sizing problems are relaxed together with integer frequencies of cutting patterns in the cutting problem. Therefore, a large scale linear optimizations problem arises, which is exactly solved by a column generated technique. It is worth noting that this new combined problem still takes the trade-off between storage costs (for final products and the parts) and trim losses (in the cutting process). We present some sets of computational tests, analyzed over three different scenarios. These results show that, by combining the problems and using an exact method, it is possible to obtain significant gains when compared to the usual industrial practice, which solve them in sequence. (C) 2010 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.

INVENTORY CONTROL SYSTEM : Optimization of production system and reliability

The main idea of this research to solve the problem of inventory management for the paper industry SPM PVT limited. The aim of this research was to find a methodology by which the inventory of raw material could be kept at minimum level by means of buffer stock level.The main objective then lies in finding the minimum level of buffer stock according to daily consumption of raw material, finding the Economic Order Quantity (EOQ) reorders point and how much order will be placed in a year to control the shortage of raw material.In this project, we discuss continuous review model (Deterministic EOQ models) that includes the probabilistic demand directly in the formulation. According to the formula, we see the reorder point and the order up to model. The problem was tackled mathematically as well as simulation modeling was used where mathematically tractable solution was not possible.The simulation modeling was done by Awesim software for developing the simulation network. This simulation network has the ability to predict the buffer stock level based on variable consumption of raw material and lead-time. The data collection for this simulation network is taken from the industrial engineering personnel and the departmental studies of the concerned factory. At the end, we find the optimum level of order quantity, reorder point and order days.