3.4 Software groups
3.4.14 Environmental decision support software
In the last few decades, mathematical and statistical models, numerical algorithms and computer simulations have been used as the appropriate means of the investigation of environmental management problems and the way to provide useful information to engineers.
To this end, a wide set of scientific techniques have been applied to environmental manage-ment problems for a long time and with good results. However, the majority of these efforts were focused on problems that can be assigned to the first level of complexity. Consequently, many complex environmental problems have not been effectively addressed by the scientific community. Recently, however, the effort to integrate new tools to deal with more complex systems has led to the development of the so-called Environmental Decision Support Systems (EDSS) (Guariso and Werthner, 1989; Rizzoli and Young, 1997).
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54 3.4.15 Specific waste management software
Although there are common features of waste management software, e.g. container tracking, routing, or the management of repetitive vehicle operations, specific tools provide additional or specialized services. Such an extension can be, for example, the possibility of customized reporting. Generally, waste management software support financial management rather than operational management. This service approach focuses on sales and billing. This is one of the main limitations. These software tools can be generally assessed as trial/demo versions, online demo or scheduled demonstration upon request (registration).
3.4.15.1 Apex WMS
The waste management software Apex WMS provides all the major tasks required by waste management companies:
• Control over operations
• Risk management
• Billing and invoicing
• Customer account management
• Reporting
• Data import and export
• Dispatch handling
• Tracking and scheduling
It is developed for waste and recycling industries (Reflective Software, 2009). The typical working screen of the software can be seen in Fig. 3.9.
Figure 3.9 Working screen of Apex WMS.
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55 3.4.15.2 IWS
Integrated Waste System (IWS) is a widely used waste management software tool (P&L Software Systems Limited, 2009). It provides waste transaction scheduling, monitoring and invoicing. IWS contains all European Waste Catalogue codes to define and identify the kind of waste the container is going to carry. It covers permit management, driver and vehicle allocation, exchange and collections. IWS records all relevant information, including the duty of care licence or the waste origin. The software tool provides landfill tax definitions, tax periods and accumulated tax calculations. Due to the built-in text translation feature it is possible to set up individual interfaces. Modularity is another useful feature of IWS.
3.4.15.3 ESS Waste
ESS Waste is a hazardous waste management software tool by Environmental Support Solutions Inc. (2009). It gathers, stores and organizes waste data, including vendor and onsite shipment, federal, provincial and state waste codes, and analytical results. Data is collected using handheld devices and/or web-based data entry forms. The software processes waste container movements, reconciliation of inventory, consolidations, and shipments, label generation, waste profiles, shipping, approved disposal facilities, and waste storage areas.
Several types of output are supported, including streamlined manifest generation, internal waste management reports, electronic regulatory reporting, and data export to Waste Reporter, a free tool of the same company. The software is SAP certified so it can be used together with the well-known business software.
3.4.15.4 WIMS
WIMS is an industrial waste management software tool developed by The Solution Works LLP (2009). The main features of WIMS are:
• Transport operations: the daily administration and control of ad-hoc work, standing order work, round-based work etc.
• Round administration: the setup and administration of round-based and standing order works
• Weigh-bridge operations: the daily administration and recording of transactions related to the weigh-bridge
• Customer service operations: take orders and respond to customer enquiries
• Sales ledger: fully functional sales ledger for contract administration and credit control 3.4.16 General optimisation tools
Even if there are some optimising features of specific software packages, it is evident that general solvers and optimisers should be applied in waste management system modelling and optimisation too. They can either modules of a mathematical software package, e.g. Matlab or Maple, or individual solvers. In the following chapters two of them are described in more detail. They are promising tools in waste management as they are already applied in practice and referred by researchers of the field (as discussed earlier in Chapter 2.2.2).
3.4.16.1 LINGO
Lingo is an optimisation modelling software for linear, nonlinear, and integer programming (LINDO Systems, 2009). It provides a fully integrated package that includes own language and interface to describe, build and edit optimisation models. These models can pull data directly from databases and spreadsheets. Lingo has a set of fast built-in solvers, including linear, nonlinear (convex and non-convex), quadratic, quadratically constrained and integer solvers, all with high precision levels (Fig. 3.10).
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56
Figure 3.10 Precision and other settings in LINGO.
LINGO comes with DLL and OLE interfaces that can be called from external applications written by the user. LINGO can also be called directly from an Excel macro or database application.
A free trial version can be downloaded for try-out.
3.4.16.2 MPL
Mathematical Programming Language, often abbreviated as MPL, is an advanced modelling system providing the formulation of complicated optimisation models in a concise and precise way (Maximal Software Inc., 2009). Models developed in MPL can also be solved with external optimisers.
MPL includes an algebraic modelling language that creates optimisation models using algebraic equations. The model is used as the basis to generate a mathematical matrix that can be relayed directly into the optimisation solver.
MPL for Windows offers a feature-rich model development environment to take the full advantage of the graphical user interface (Fig. 3.11).
It is capable to import data directly from databases or spreadsheets. Once the model has been solved, MPL can export the solution back into the database. MPL models can be embedded into other Windows applications, including databases and spreadsheets.
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57
Figure 3.11 Graphical user interface of MPL for Windows.
3.5 Comparisons
A substantial part of techniques and methodologies for availability and reliability calculations is known for decades. This is the reason why complex RAM/RAMS software packages have many similar or overlapping features. They compete by offering additional modules or some extra services. General comparisons were made by focusing on the special capabilities of four advanced packages: the Relex Reliability Studio (Chapter 3.4.11.1), the ITEM (Chapter 3.4.11.2), Isograph (Chapter 3.4.11.3) and ReliaSoft (Chapter 3.4.11.4) packages. Their differences are summarized in Table 3.4.
One of the first aspects for examination is the graphical user interface together with user-friendliness. Although widely used solutions are common within these software suits, including menus and tabs, there are plenty of exceptions too. The main reason for this is the modular structure of complex reliability packages and the services provided by many of them.
These are the interaction between these modules, considering the relationships between the tables of databases and the associated graphical representations, including all types of reliability diagrams. While the working approach varies from package to package, it is difficult to make a concluding recommendation for only one software package, due to the different needs.
Generally, the graphical user interfaces of these modern packages have more or less the same level of usage complexity.
Another feature, offered by only a limited number of packages, is customizability. In the ITEM software suit, for example, even user-defined component libraries can be used.
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Table 3.4 General comparison of reliability software candidates.
Feature
User-friendliness very good good very good good
License options normal normal normal wide
Support very good good good very good
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59
An important feature to consider is the support of industry standards. The more standardized they are, the easier to use them for modelling real life applications. It is worth to take a look at the industries or even specific companies where these software packages are used.
Both of the two major analysis and calculation approaches, analytical approach and simulation, are supported by the biggest packages. Especially the second one can hardly be found in small reliability software tools.
Most of these software suits give fine graphical outputs providing results of modelling, reliability analysis and calculations. They can be printed out directly or exported into the most widely used bitmap and vector formats for further usage.
More specific assessments about calculation power can be found in the case studies (Chapter 6).
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CHAPTER 4
RESEARCH APPROACH
The research conducted by the research group of the Author combined theory and practice in a unique way. The description could not form a rounded whole without mentioning the occurrent problems and the limitations, among the structure of the research.
4.1 Objective of the research
The original aim of the research was to contribute to both the theoretical and practical modelling and optimisation of waste management issues through software methodologies. It has succeeded, however, the way to achieve this aim was not straightforward in terms of software assessment and investigation of real life data.
4.2 Limitations
Although the research topic was promising, there were some limitations that need to be mentioned. Like any other industrial process engineering fields, waste management requires significant time durations to perform thorough analyses and provide a realistic picture. The expected lifetime of many components in waste management systems are much longer than the duration of the PhD research. However, software features such as estimation, prediction and simulation were needed to investigate the software possibilities and develop software methodologies. It was the solution for the above problem. As a result, these methodologies provide both the estimation of current probability of failure and the prediction (or simulation) of future probability of failure.
A further limitation of time was the lost potential to develop own software tools for waste management reliability modelling and optimisation.
Another problem was to find plants for industrial experiences. Because waste management varies from region to region, it was crucial to find plants from different scenarios in order to get a sufficient understanding of real life applications.
4.2.1 Data collection
There is a wide variety of waste data and they are hard to collect. Research on this field requires lots of time and patience. Waste management companies and incinerators try to avoid publicity. They do not want to provide data, even for research purposes. The reason for this behaviour is easy to understand: there is no need to prove effectiveness, the environment-friendly feature of processes, or to compete with other companies. However, this approach made the research more difficult. Those modern plants that are built or improved recently and are ready to provide data are on a different level of reliability due to their new items and the advanced technologies applied in them. The probability of failure is rather low and in such cases the importance of estimation and simulation is much more than that of calculations.
Research approach
61 4.2.2 Analyses
The application of various software tools for modelling and optimising RAM issues of waste management systems involves much potential. The analysis of waste management failure history can be used for calculating RAM for the given period. If data are not exact or some are missing, it is still possible to estimate RAM.
For most availability analyses, availability for waste treatment was defined first to construct the availability logic diagram, followed by data collection. Finally, calculations were performed with various software tools. Beyond failure and repair data, distributions of failure and repair times were collected.
The research group estimated current probabilities of failures with software support.
Furthermore, the applied software packages were capable to do even more: future probabilities of failures were predicted with them.
4.2.3 Simulation
The research group applied simulation in many cases in order to solve the problem of missing data or generate data for various scenarios. These data sets could be used for comparisons and the investigation of future failures with the highest probability of occurrence.
For research purposes, both analytical methods and simulation were used.
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CHAPTER 5
PROPOSED METHODS IN WASTE MANAGEMENT SYSTEM ANALYSES
Waste treatment and waste management systems and techniques have been developed in recent years to reduce the environmental burden and to address energy production. They affect environmental protection and quality of life considerably. The challenge facing the modern society is growing. There is a strong need to identify and implement long-term solutions that are safe, socially acceptable, and cost-effective at the same time. The amount of waste produced by the civic population (MSW), the industry (IHW) and agriculture, respectively, requires the application of efficient waste disposal techniques. The MSW management is a fast growing problem that goes hand in hand with the growing concentration of the population in large cities. New and advanced approaches of MSW management should implement advanced tools. The problem has been extensively studied from the technological point of view. However, the importance of availability and reliability issues of waste management and especially MSWM deserve extended attention.
5.1 Mathematical models for RAM optimisation in waste management
New mathematical models were introduced for RAM optimisation in waste management.
They cover some specific WMS parts and consider all the features that affect availability, reliability and maintainability. The following ones were considered in each model in addition to the specific statements and assumptions described along with the definitions:
• Consider repairable and non-repairable system components
• Distinguish series and parallel subsystems
• Consider the changes of unit failure rates according to age and replacement
• Differentiate operating classes
• Handle independent, mutually exclusive and conditional probability of failure
• Identify units in partial operation 5.1.1 Solid waste combustion models
Two solid waste combustion models were introduced by the Author, namely the reliability model for waste drying and that of energy conservation, respectively. The models were prepared for a two-stage reciprocating waste incinerator where the waste undergoes drying, pyrolysis, and combustion along the grate after entering the incinerator.
The distributions of temperature, wastes and mass flowrate of gas are non-uniform. The temperature of the gas from the drying and pyrolysis sectors is lower, and contains lots of oxygen and unburned hydrocarbon. The gas from the combustion zone is hotter and scarce in
Proposed methods in WMS analyses
63
oxygen. These gases will then mix with the secondary air and burn in the combustion chamber above the waste bed, while exchanging heat with the waste bed and furnace walls.
Both models apply assumptions. The initial assumptions are used to form the basic (ideal) case. Later, these models will be extended in order to meet all criteria. The solid waste entering the process is homogenous. The operation of the thermal treatment plant is stable. This assumption can be avoided by perturbating the process with reliability. Additionally, it is assumed that the waste moves continuously with contstant speed in the direction of the grate.
Again, this should not be included if availability and reliability are taken into account. The height and width of waste are within the allowable constraints. The treatment of bulk wastes can be considered for more realistic modelling. For the basic models, the heat exchange between the furnace wall and the surrounding areas was not included. The distributions of temperature and species, used as the boundary conditions of gas phase combustion above the bed, are determined by the numerical simulation of solid waste burning.
5.1.1.1 Availability model for waste drying
Due to the variety of waste management equipment units and technologies it is hard to set general models. Thus the system type should be well defined. The mathematical model of the Author was developed for two-stage reciprocating waste incinerators where solid waste reaches the drying process after entering the plant. Heat and water mass transfers are simultaneous and are in opposite directions. Furthermore, there are some assumptions for which the definitions held. Most important of all, it is assumed that all units should be available in order to achieve overall availability. The operation of the thermal treatment plant is stable. The solid waste that enters the incinerator is originally homogenous. Waste velocity should be constant.
The availability of air transfer for such cases can be defined as
( )
where i represents all combustor units to consider. Typically they are the following units:
inlet fan, decoupling chamber, mixing chamber, membrane valve for inlet air, pressure transducer, pipe to dryer, anti-explosion valves, nozzle, drying chamber. The list of units depends on the type of the dryer and can be customized according to it.
j represents measuring apparatus including
• Temperature sensors for measuring air temperature t [°C]
• Air density measurement equipment for measuring air densityρa [kg/m3]
• Air velocity meter for measuring velocity va [m/s]
• Humidity meters for measuring the difference between absolute outlet and inlet air humidity, i.e. Hao and Hai [kg/kg]
Note that the main assumption can be missed and Eq. 5.1 altered for more specific definitions. Thus the equation can be customized.
5.1.1.2 Reliability model for thermal treatment
The probability of failure occurrence of equipment units in two-stage reciprocating incinerators can be described as
(
P P1∩ 2)
⋅(
P3∪ ∪P4 P5) (
⋅ P6∪ ∪P7 P P P P P8)
⋅ ⋅ ⋅ ⋅P S T(
9∪P10∪P11)
(5.2)where the numbers denote the probability of failure occurrence in the following equipment units:
Proposed methods in WMS analyses 8) Refractory wall (combustion chamber) 9) Ports
10) Temperature sensors 11)Sampling tubes or LASER
P represents the magnetic, S the non-ferrous and T the pneumatic separators, respectively.
Since P9, P10 and P11 are, in contrast with P3, P4, P5 and P6, P7, P8, mutually exclusive, the probability of separator failures should be calculated differently as described in probability theory.
The reliability of solid waste combustion in thermal treatment plants described above can be defined as
The model was developed with focus on units that are required for burner processes. It can be extended with the number of sensors, other equipment units and further subsystems of treatment plants.
5.1.2. Optimisation model for reliability of waste recycling
Waste recycling can be performed in various ways. The model introduced by the Author considers the reliability of equipment units from collection and transportation through material recycling andreprocessing. It includes the separation of materials into their constituent parts. The reliability of recycling for such systems, in general, can be defined as
1 1 RC is the reliability of separate waste collection facilities for recycling paper, heavy plastic, plastic bags, plastic bottles, glass, organic material, wood, metals, textiles etc. Such values can be used for decision variables in optimisation. RM is the reliability of material recycling facilities such as conveyor belt, magnets, and screening devices. RS is the reliability of equal spares. RR is the reliability of reprocessors that handle the various materials including heater for metal and glass, coverters for plastic to produce granulate or pellet, the pulper and shredder facilities for paper and so on. Their reliability factors are therefore mutually exclusive. The small letters represent the following:
• n is the number of separate waste collection facilities
• m is the number of material recycling facilities
• p is the number of reprocessing facilities
• q is the number of equal spares
Scraps, residues and inert matters sent to recycling can be considered as well upon request
Scraps, residues and inert matters sent to recycling can be considered as well upon request