Nach oben pdf Recovery planning method for production systems

Recovery planning method for production systems

Recovery planning method for production systems

Only [MT02] has a YES in both categories but this method is applied in the engineering phase. It is a viable approach to assess the different EoL scenarios in the engineering phase so that the system is engineered or designed in accordance with the chosen EoL scenarios. A disadvantage is that this decision is based on assumptions due to the lack of data at this point. Also, a production system compared to a product has a longer operation phase. Production systems can operate between several years up to decades. After years of operating, the production systems could have changed, market or legal regulations might have changed, new EoL technologies are available, or prices for materials have increased or decreased. This all could affect the decision for a proper EoL scenario. Therefore, such an assessment for a suitable EoL scenario should be executed or repeated when the production system has reached its end of life. In addition, [MT02] always has the same recovery goal: the product. For it, the different EoL strategies are considered. For example: Is it better to repair a component of the product, or is it better to recycle the material, process this recycled material again to a new component, or is it even better to throw the old component away, process natural resources/virgin materials to a new component which is, then, assembled again into the product? And which of these EoL strategies makes the product in the end cheaper, more green, or more technological advanced? But the author thinks another viewpoint is needed here and, therefore, different recovery goals should be available. This thesis is about analyzing the different options or treatments of a production system at the end of its life. And it is obvious that in case a lot of inherent value is destroyed the more effort is needed to produce an equivalent value. But components and material might not end up in another production system. Instead they could leave the production system life cycle and start a new life in another life cycle.
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The Use of Optimal Management Tasks for Verification and Adjustment of New Product Release Planning in Discrete Production Systems

The Use of Optimal Management Tasks for Verification and Adjustment of New Product Release Planning in Discrete Production Systems

Currently, we observe a trend when life cycle is reducing and the range of products is increasing. In discrete productions it leads to new problems of search and integration of new products, product line, modification selection. For all that, decision making is affected by external market environment that is not predetermined yet. The task gets more complicated because of the continuity of production process that consists in the peculiarities of a performed operation, such as in-line assembly, stamping operations, casting, pressing, etc. From the other hand, there is a trend for enhancing the versatility of production tools that sets advanced requirements to management decision making and planning as the interchangeability of industrial machinery causes the
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Cost-optimal spare parts inventory planning for wind energy systems

Cost-optimal spare parts inventory planning for wind energy systems

Internal maintenance cost include cost for maintenance measures itself, supply of raw material, resources, tools and spare parts as well as depreciation for operative units. Depreciation costs accrue for wearing components oper- ating many periods. They are based on the units’ price and the length of the life cycle. The second cost factor, costs for service providers, complies with the service contract between the service provider and the machine operator. It varies with terms of services, for example if spare parts and repair cost are included, the operator of the machine does not have to realize spare parts planning. If a failed unit destroys other units, secondary damages are the conse- quence. The fourth cost factor comprises additional expenses, which are common in production, because it is often possible to produce more goods in advance and, herewith, compensate loss of production costs. Costs for secondary damages as well as costs for additional expenses are neglected in the following, because secondary damages arise randomly and additional expenses cannot avert con- sequences of machine downtime in the field of wind energy. Costs for machine downtime include costs for lost sales or, in case of wind energy business, missing remu- neration for feeding electricity into the grid. The costs are determined by the feed-in tariff, the power of the wind turbine, the share of full load hours as well as the duration of the breakdown (Eq. 2 ).
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Production Planning with Simulated Annealing

Production Planning with Simulated Annealing

k → ∞ T k = 0. For any fixed value of the con- trol parameter a homogenous markov chain is generated. A markov chain is a series of con- figurations where a configuration Y only depends on the last accepted configuration X. The second kind of formulation of the method is that one as an inhomogenous algorithm. Then after each step the control parameter is reduced. So the proceeding is described as an inho- mogenous markov chain . Theoretically both formulations converge asymptotically to a global optimum with a probability of one when certain conditions are held [Laarhoven, Aarts 1992]:
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Literature review of optimization based decision model for  disaster recovery planning  of transportation network

Literature review of optimization based decision model for disaster recovery planning of transportation network

16- Shanshan, H., Wenhai, Z., Chaofeng, W., 2015. Collaborative Dynamic Optimization on Post-earthquake Emergency Supply and Road Rehabilitation Based on Road Network Connectivity, The Open Automation and Control Systems Journal, 7: 1398- 1404, [DOI: 10.2174/1874444301507011398]

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Integrated Planning and Control for Collision Avoidance Systems

Integrated Planning and Control for Collision Avoidance Systems

The design of the proposed methods in this thesis focused on the requirements and scenarios for evasive collision avoidance maneuvers in an advanced driver assistance system. In the future, the proposed framework has big potentials for general automated driving tasks where the driver is out of the control loop. Fur- ther, the design goals may be modified to integrate traffic rule information into the method such as the maximum allowed speed and the traffic light status. High standards are set for trajectory planning and vehicle dynamics control modules in order to enable automated driving functionality. The proposed fast integrated planning and control method lays the foundation for the full exploita- tion of the available vehicle dynamics and the available space during the ma- neuver execution. The design concepts investigated in this thesis are promising to accelerate the realization of future design principles and thereby contribute to the overall development of automated driving technologies.
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Identifying behavior models for hybrid production systems

Identifying behavior models for hybrid production systems

automaton structure (states and transitions), as well as two probability distributions: probabilities of the events (symbols that trigger transitions), and time probabilities. These distributions are assumed to be independent. In addition to merging, a splitting step is also introduced. The decision whether to merge two states or split a single state is based on the likelihood-ratio test that gives the p-value. High p-value indicates that two states are similar and can be merged. Low p-value indicates that a state should be split. If a split of a state is found that results in a p-value lower than 0.05, the split with the lowest p-value is performed. If a merge is found with the p-value larger than 0.05, the merge with the largest p-value is performed. Alternatively, other statis- tical tests can be used, such as the Kolmogorov-Smirnov test and Fisher’s method [Ver10]. Verwer shows that by increasing the amount of learning data, the p-value resulting from any used test converges to zero for two different states. Therefore, in the limit such states will never be merged (p-value greater than 0.05 is needed to make a merge). Although some extra splits are possible, they do not influence the correctness of the learned language, but only increase the model size. Statistical tests are computed in polynomial time for every state. In addition, the algorithm makes maximum 2n 2 + n iterations, where n is the size of the input sample. Thus, the runtime of the RTI+ algorithm is polynomial in the size of the input data. u t Corollary 7. Previous theorem implicitly proves that PDRTAs are IDLimitProb1.
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A heuristic method for measurement site selection in sewer systems

A heuristic method for measurement site selection in sewer systems

Abstract: Although calibration of a hydrodynamic model depends on the availability of measurement data representing the system behavior, advice for the planning of necessary measurement campaigns for model calibration is scarce. This work tries to address this question of efficient measurement site selection on a network scale for the objective of calibrating a hydrodynamic model case study in Austria. For this, a model-based approach is chosen, as the method should be able to be used before measurement data is available. An existing model is assumed to represent the real system behavior. Based on this extended availability of “measurement data” in every point of the system, different approaches are established to heuristically assess the suitability of one or more pipes in combination as calibration point(s). These approaches intend to find suitable answers to the question of measurement site selection for this specific case study within a relatively short time and with a reasonable computational effort. As a result, the relevance of the spatial distribution of calibration points is highlighted. Furthermore, particular efficient calibration points are identified and further measurement sites in the underlying network are recommended.
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Production key figures for planning the mining of manganese nodules

Production key figures for planning the mining of manganese nodules

Conclusion Potential mining fields can be found in plain areas embedded in horst and graben structures. Bulk-mining would leave pat- chy areas scattered on the seafloor. In the case of eastern Ger- man license area, the geology favors a strip-like mining pattern in NNE-SSW direction. Production from a single Blue Mining or comparable system is likely limited to 1.5–2 Mt SMnN per year, mainly due to geological, technical, and operational rea- sons. Time efficiency, i.e., annual operating time at full mining capacity has emerged to be the largest unknown factor to access future mining systems. Further research and pilot- mining tests are necessary to gain a better understanding of the geology, technical, and economic feasibility and environ- mental footprint of SMnN mining. Although results are marked by uncertainty, the presented mapping technique and provided formulas to calculate PKFs are a step forward to technically and economically dimension an SMnN mining system. Parallels to agricultural engineering regarding machine, land, and resource management become obvious.
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Separable programming for aggregate production planning: A high-order cost case

Separable programming for aggregate production planning: A high-order cost case

University of Stellenbosch Business School (USB), Bellville, South Africa Suggested Citation: Meij, J. T. (1982) : Separable programming for aggregate production planning: A high-order cost case, South African Journal of Business Management, ISSN 2078-5976, African Online Scientific Information Systems (AOSIS), Cape Town, Vol. 13, Iss. 1, pp. 18-22,

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A new heuristic and an exact approach for a production planning problem

A new heuristic and an exact approach for a production planning problem

We deal with a very complex and hard scheduling problem. Several types of products are processed by a heterogeneous resource set, where resources have different operating capabilities and setup times are considered. The processing of the products follows different workflows, allowing also assembly lines. The goal is to process all products in minimum time, i.e., the makespan is to be minimized. Because of the complexity of the problem an exact solver would require too much running time. We propose a compound method where a heuristic is combined with an exact solver. Our proposed heuristic is composed of several phases applying different smart strategies. In order to reduce the computational complexity of the exact approach, we exploit the makespan determined by the heuristic as an upper bound for the time horizon, which has a direct influence on the instance size used in the exact approach. We demonstrate the efficiency of our combined method on multiple problem classes. With the help of the heuristic the exact solver is able to obtain an optimal solution in a much shorter amount of time.
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Production key figures for planning the mining of manganese nodules

Production key figures for planning the mining of manganese nodules

Conclusion Potential mining fields can be found in plain areas embedded in horst and graben structures. Bulk-mining would leave pat- chy areas scattered on the seafloor. In the case of eastern Ger- man license area, the geology favors a strip-like mining pattern in NNE-SSW direction. Production from a single Blue Mining or comparable system is likely limited to 1.5–2 Mt SMnN per year, mainly due to geological, technical, and operational rea- sons. Time efficiency, i.e., annual operating time at full mining capacity has emerged to be the largest unknown factor to access future mining systems. Further research and pilot- mining tests are necessary to gain a better understanding of the geology, technical, and economic feasibility and environ- mental footprint of SMnN mining. Although results are marked by uncertainty, the presented mapping technique and provided formulas to calculate PKFs are a step forward to technically and economically dimension an SMnN mining system. Parallels to agricultural engineering regarding machine, land, and resource management become obvious.
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Artificial Learning Dispatch Planning for Flexible Renewable-Energy Systems

Artificial Learning Dispatch Planning for Flexible Renewable-Energy Systems

As a drawback, classical decision trees are highly unstable with respect to minor perturbations in the training data. Also, each tested input set follows one fixed rule and, therefore, has always one fixed output associated with it. In many cases, it would be interesting to have several rules related to similar input sets, leading to several output with different probabilities. Fuzzy logic brings an improvement in these aspects due to the elasticity of fuzzy sets formalism [ 18 ], and therefore a fuzzy decision tree technique can enhance the learning, already applied with success in several areas [ 25 ]. A fuzzy decision tree method is presented by [ 26 ], resulting in output with much lower variance than for standard trees, as a direct cause of the improved accuracy. A modification to combine decision trees with fuzzy representation is outlined by [ 23 ] with the intent to exploit complementary advantages of standard and fuzzy decision trees: the popularity of learning from examples and high knowledge comprehensibility of decision trees; and the ability to deal with inexact and uncertain information of fuzzy representation. The results obtained are shown to be most suitable for problems with both numerical and symbolic features, when the goal is high knowledge comprehensibility and gradually changing output. A fuzzy decision tree method applied to voltage collapse assessments has been developed by [ 27 ]. A fuzzy extension to decision trees is proposed by [ 28 ], considering the basic concepts of probability and utility theory.
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Models and methods for supporting lot sizing decisions in product recovery systems

Models and methods for supporting lot sizing decisions in product recovery systems

One of the main topics in these contributions is the assessment of joint lot sizing deci- sions for remanufacturing and manufacturing which has been thoroughly investigated in recent years. One of the first authors who established a basic modeling approach is Schrady ( 1967 ) who develops a simple solution procedure for determining the lot sizes of repair and manufacturing lots. He assumes in his work that a constant and contin- uous demand for a single product has to be satisfied over an infinite planning horizon. Furthermore, a constant return fraction is established that describes the percentage of used products that return to the producer. By using that assumption, a constant and continuous return rate is ensured. Presuming setup costs for remanufacturing and manufacturing as well as different holding costs for repairable and newly manufactured products, a simple EOQ-type formula (with EOQ being the economic order quantity) is proposed that minimizes the sum of setup and holding costs per time unit. As a result, an efficient cyclic pattern is established which is characterized by the fact that within each repair cycle a number of repair lots of equal size succeed exactly one manu- facturing lot. By solving the proposed EOQ-formula which can be applied because an infinite production and repair rate is presumed as well, the number of repair lots and the length of a repair cycle can be determined. Teunter ( 2001 ) generalizes the results of Schrady in a way that he examines different structures of a repair cycle. He adds to the efficient cycle patterns a cycle in which several manufacturing lots of equal size are followed by exactly one repair lot. The assumption of equal lot sizes is among other aspects critically studied in the contribution of Minner and Lindner ( 2004 ). They show that a policy with non-identical lot sizes can outperform a policy with identical lot sizes. However, the structure of an efficient repair cycle prevails also when the assumption of equal lot sizes is lifted.
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A simulation-based method for improving material efficiency within the constraints of existing production systems

A simulation-based method for improving material efficiency within the constraints of existing production systems

SD is traditionally applied at the macro level to investigate population dynamics, competition on the marketplace, and ecosystems (Borshchev 2004, pp. 3). Mathematically SD simulations are a set of differential equations, with variables modelled as stocks (e.g. city population or the volume of water in a bath), flows (changes in stocks), and auxiliary variables, which determine the values of the flows. SD simulations are generally concerned with the progression of the stock variables over time. Feedback loops and self- amplifying or balancing effects are most easily demonstrated in SD models. In manufacturing SD models, the manufacturing rate of a process is seen as a flow, emptying the stock of raw material and filling the stock of processed material. Unlike the entities of a DES diagram, the material in an SD flow must be homogeneous. Therefore, multiple, linked SD flows are utilized to model multi-variant production.
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Comparing two computer search models for aggregate production planning

Comparing two computer search models for aggregate production planning

University of Stellenbosch Business School (USB), Bellville, South Africa Suggested Citation: Meij, J. T. (1982) : Comparing two computer search models for aggregate production planning, South African Journal of Business Management, ISSN 2078-5976, African Online Scientific Information Systems (AOSIS), Cape Town, Vol. 13, Iss. 2, pp. 67-69,

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Monitoring agricultural productivity for sustainable production and R&D planning

Monitoring agricultural productivity for sustainable production and R&D planning

_________________________ 7 We can argue that proper accounting for quality and price effects in terms of marketed inputs while doing TFP accounting can properly capture the role of private R&D. However, public R&D contribution requires additional treatment and analysis. 8 Using lagged flows of expenditures without doing a true perpetual inventory and mixing two separate problems: adoption delays and knowledge depreciation using small weights for early years and for the most recent periods. Using one distribution to mimic two different behavioral issues has clear limitations from a structural point of view and policy recommendations. It also implies that analysts using this method, assume a complete decay of some innovation over time. For instance, the lag assumptions made in most of the literature lead to the implicit conclusion that Dr. Norman Borlaug’s work on semi-dwarf wheat varieties have no impact on existing stock of knowledge, and therefore productivity.
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Optimization of the Reconfiguration Planning of Cyber-Physical Production Systems

Optimization of the Reconfiguration Planning of Cyber-Physical Production Systems

First, it is tried to reduce the configuration space by preceding analyses of mandatory requirements as resulting from parametric relations of the design parameters based on practical implementation, kinematic characteristics, and perfor- mance criteria. Solving the resulting constraint satisfaction problem, the initial intervals for the design parameters are drastically reduced by preliminary considerations and analyses only before starting the actual optimization procedure. At the same time, the solution space is reduced without discarding viable candidates based on poor user experience. Second, it is tried to enhance the performance of the initial formulation as so-called p-median problem (which was orig-
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Holistic integration of a VR solution into the planning process of scalable production systems

Holistic integration of a VR solution into the planning process of scalable production systems

Using a VR-framework leads to no costs of integration since the framework can be used by the planners as a replacement for their existing tools. Therefore, this option is rated very good. Cost for licenses are rated bad for the implementation through a service provider. In a pilot project conducted during this work, the implementation of one workstation costs 10.000€. Considering five production lines with combined more than 100 workstations, costs would add up to more than 1 Mio. €. Programming in game engines would only require licenses for the chosen game engine and a converter program to convert the given CAD-data into VR data. Those licenses would add up to a maximum of 10.000 € a year regardless how many stations are implemented. Therefore, a rating as very good was evaluated here.
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Benefit Oriented Production Data Acquisition for the Production Planning and Control

Benefit Oriented Production Data Acquisition for the Production Planning and Control

next. The job of capacity control is to determines the actual capacities usage and decides about extra hours and staff distribution. [3] Since the mentioned tasks are strongly connected to the shop floor, a high traceability and resolution of production processes is of high importance to enable efficient PPC processes. Depending on specific controlling methods, each task requires different information that should be collected on the shop floor. For that purpose, many information and communication technologies (ICT) are available on the market. Typical solutions to acquire feedback from the shop floor automatically are barcode and radio-frequency identification (RFID) technology which pertain to the group of auto-ID solutions. Other comparatively cheap technologies for PDA are e.g. OCR, terminals, beacons or cameras. PPC related production data such as the starting or the end time of setting up a machine, can be collected through workers scanning barcodes on production orders or through RFID sensors recognizing a transponder within their reading area. Whereas barcodes are already commonly used, RFID solutions gain increasing popularity, especially because of easy handling and higher data storage. The big disadvantage of the RFID technology is its perturbation in metallic surroundings. An even higher information resolution than with RFID can be gained through real time localization systems (RTLS) that are mostly based on Wi-Fi and enable a continuous traceability of objects through the entire production. The drawback of RTLS technology is, that compared to barcode or RFID technology it is quite expensive and bulky.
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