Complexity of production processes, high computing capabilities, and massive datasets characterize today’s manufacturing environments, such as those of continuous andbatch production industries. Continuous production has spread gradually acrossdifferent industries, covering a significant part of today’s production. Commonconsumer goods such as food, drugs, and cosmetics, and industrial goods such as iron,chemicals, oil, and ore come from continuous processes. To stay competitive intoday’s market requires constant process improvements in terms of both effectivenessand efficiency. Statistical process control (SPC) and design of experiments (DoE)techniques can play an important role in this improvement strategy. SPC attempts toreduce process variation by eliminating assignable causes, while DoE is used toimprove products and processes by systematic experimentation and analysis. However,special issues emerge when applying these methods in continuous process settings.Highly automated and computerized processes provide an exorbitant amount ofserially dependent and cross-correlated data, which may be difficult to analyzesimultaneously. Time series data, transition times, and closed-loop operation areexamples of additional challenges that the analyst faces.The overall objective of this thesis is to contribute to using of statisticalmethods, namely SPC and DoE methods, to improve continuous production.Specifically, this research serves two aims: [1] to explore, identify, and outlinepotential challenges when applying SPC and DoE in continuous processes, and [2] topropose simulation tools and new or adapted methods to overcome the identifiedchallenges.The results are summarized in three appended papers. Through a literaturereview, Paper A outlines SPC and DoE implementation challenges for managers,researchers, and practitioners. For example, problems due to process transitions, themultivariate nature of data, serial correlation, and the presence of engineering processcontrol (EPC) are discussed. Paper B further explores one of the DoE challengesidentified in Paper A. Specifically, Paper B describes issues and potential strategieswhen designing and analyzing experiments in processes operating under closed-loopcontrol. Two simulated examples in the Tennessee Eastman (TE) process simulatorshow the benefits of using DoE techniques to improve and optimize such industrialprocesses. Finally, Paper C provides guidelines, using flow charts, on how to use thecontinuous process simulator, “The revised TE process simulator,” run with adecentralized control strategy as a test bed for developing SPC and DoE methods incontinuous processes. Simulated SPC and DoE examples are also discussed.

Syftet med detta examensarbete har varit att ta fram vilka leanprinciper och leanverktyg som passar en processindustri med målet att minska ledtiden. För att kunna genomföra studien har en jämförelse mellan teori och verklighet gjorts där hjälp tagits av Lesjöfors industrifjädrar AB. Utmärkande aspekter för företagets produktion är långa led- och omställningstider, produktion i batcher med stora partistorkekar samt tryckande tillverkning. Litteraturstudien omfattar fem principer och fem verktyg. För att identifiera nuläget har en värdeflödeskartläggning genomförts samt intervjuer med anställda på företaget. När teori kopplas med empiri har lämpliga principer och verktyg utifrån de studerade 10 valts ut. De principer som har identifierats som lämpliga för en processindustri är standardiserat arbetssätt, ständiga förbättringar, utjämnad produktion. De verkyg som utefter principerna identifierats som lämpliga är SMED, 5S samt värdeflödeskartläggning. Dessa har sedan används i en sammanfattning i form av ett TPS-hus, unikt för produktionen på Lesjöfors industrifjädrar AB. / The aim of this bachelor thesis has been to identify which lean principles and lean tools that would suit a process industry with the goal of reducing lead times. In order to complete the study, a comparison between theory and reality has been made where assistance has been provided by Lesjöfors industrifjädrar AB. Key aspects of the company's production include long lead times and set up times, production in batches with large lots and push production. The literature study comprises five principles and five tools. To identify the current situation, a value stream mapping has been conducted and interviews with employees at the company. When theory is linked with empirical studies, suitable principles and tools based on the selected 10 have been chosen. These have then been used in a summary in the form of a TPS-house, unique to the production at Lesjöfors industrifjädrar AB.

To make a difference among the energy intensive process industries, this dissertation addresses production planning and supply chain planning problems related to industrial energy management issues. The energy issue is turning more and more important from different angles, involving price as well as environmental problems due to climate change leading to political pressure on all energy users. The process industry sector is one of the largest users of energy, and thus important to analyse. Process industries are also capital intensive and operate on large and expensive process equipment, making it imperative to plan their production well in order to reach preferable capacity utilisation. Therefore this dissertation strives to locate the most important energy management issues for the long term profitability of process industries, and investigates the  symbiotic effects of including energy issues in production and supply chain planning. Three different studies at three case companies are carried out, analysed, and presented in five papers. The cases represent the process industry sectors: chemicals, pulp, and steel. Both qualitative case study methodologies as well as quantitative mathematical modelling and optimisation approaches have been practiced. The research questions are analysed from both an energy system and from a production process point of view, separately as well as combined. Energy is somewhat considered to be the main workforce for process industries and this dissertation exemplifies some of its most important dimensions in this context. Several prerequisites for putting energy management on the strategic agenda are located in a specialty chemical industry where the importance of introducing a strategic perspective on energy, the way energy is used, and the possibilities of increasing alternative revenue from utilising by- and/or co-products differently are pinpointed. Approaches for including energy issues in planning processes are also suggested in terms of a MILP model for the entire supply chain of a pulp company, including decisions on purchase and transportation of raw maerials, production allocation, energy mix, and distribution. Another example is presented based on the perspectives of economics of scale and lot sizing through economic order quantity principles in a steel company. By using real company data, energy smart approaches in planning and scheduling are developed with respect to the most important intersections between the production processes and their supporting energy system. The accumulated resource intensity and embedded energy could, and probably should, hence be more fairly  reflected in the product price. The research finally shows some possible impact with including energy issues in a production and supply chain planning model. By planning differently, production prioritisations can be done, and it is not only possible without any large investments, but also prosperous with savings on both energy and money within reach. To conclude, planning of production and supply chain has either a direct or an indirect impact on the energy cost-effectiveness of a company. This dissertation argues that such impact also exists in its mutual form, and is very important when the energy issues are large enough, as they often are in the energy intensive process industry sector. Decision makers should thus beware of the short end of the stick that might be  devastating in the long run, but also aware of all the possibilities that can bring success and prosperity when the future begins.

La thèse s’intéresse au travail de conduite d’une industrie de process à risques,les centrales nucléaires, et aux marges de manoeuvre dont disposent les équipes dans l’application des procédures techniques. Celles-ci doivent en effet être adaptées aux situations rencontrées dans la réalité, qui sont toujours nouvelles et finalement uniques. En effet, la technologie concernée est si complexe que les situations ambiguës sont fréquentes. Les exploitants sont souvent confrontés à des décisions techniques qui cristallisent en elles la pluralité d’exigences auxquelles sont soumises les industries à risques : sûreté nucléaire, disponibilité et productivité, sécurité des travailleurs, respect de l’environnement, etc.Exploiter une centrale nucléaire implique donc d’arbitrer entre des exigences qui devraient en théorie être conciliables mais qui ne le sont pas en pratique, ou difficilement. En effet, chaque terme de la décision concrète comporte des avantages vis-à-vis de l’un des critères et des inconvénients vis-à-vis des autres critères en présence. Ainsi, décider revient toujours à renoncer, et la décision technique dans les organisations à risques implique une prise de risque professionnelle et personnelle pour les acteurs de terrain. La thèse s’interroge alors sur les facteurs qui participent de l’engagement des opérationnels dans l’action. Les théories utilitaristes et culturalistes ne parvenant pas à épuiser toute la complexité des cas rencontrés (implication d’agents pourtant peu carriéristes, disparités individuelles fortes au sein de groupes socio-professionnels supposés homogènes. . .), la recherche s’intéresse aux théories de la reconnaissance sociale et du don/contre-don comme explication première de la motivation et de la coopération au travail. / This doctoral dissertation describes the running of a high-risk process industry,nuclear power plants, and the operators’ autonomy to apply technical procedures.The chosen procedures must fit the "real-life" situations, which are always new, andultimately unique. Nuclear power technology is so complex that ambiguous situations often arise. The operators have to make technical decisions that encompassall the demanding issues of high-risk industries : nuclear safety, plant availabilityand generation output, workers’ safety, environmental protection, etc.Operating a nuclear power plant thus involves trade-offs between theoretically compatible concerns that in practice are incompatible or difficult to reconcile.Each option in the actual decision will have advantages for certain criteria anddisadvantages for others. Deciding thus always means forgoing something, andtechnical decision-making in high-risk organizations forces the field workers totake professional and personal risks. The dissertation thus examines the factors explaining why operators are still interested in getting involved in the action.Self-interest and cultural theories cannot explain all the cases encountered in thefield (workers with high commitment but paradoxically little interest in career advancement, strong differences between individuals in a supposedly homogenoussocio-professional groups, etc.). The research focuses on social recognition andgift/countergift theories as the primary explanation for motivation and cooperation at work.

Submitted by Livia Mello (liviacmello@yahoo.com.br) on 2016-09-28T18:01:55Z No. of bitstreams: 1 DissGCM.pdf: 2068084 bytes, checksum: 4d89da9569508f8b5d13a8b899ad055a (MD5) / Approved for entry into archive by Marina Freitas (marinapf@ufscar.br) on 2016-10-04T19:00:31Z (GMT) No. of bitstreams: 1 DissGCM.pdf: 2068084 bytes, checksum: 4d89da9569508f8b5d13a8b899ad055a (MD5) / Approved for entry into archive by Marina Freitas (marinapf@ufscar.br) on 2016-10-04T19:00:38Z (GMT) No. of bitstreams: 1 DissGCM.pdf: 2068084 bytes, checksum: 4d89da9569508f8b5d13a8b899ad055a (MD5) / Made available in DSpace on 2016-10-04T19:00:49Z (GMT). No. of bitstreams: 1 DissGCM.pdf: 2068084 bytes, checksum: 4d89da9569508f8b5d13a8b899ad055a (MD5) Previous issue date: 2015-12-14 / Não recebi financiamento / The quest for increased productivity has become a mantra repeated ad nauseam in many companies immersed in a globalized market. In this context, many computational techniques have becoming more popular, gaining followers, aiding and refining the process of decision-making. Among the various techniques available, the discrete event simulation stands out, as it allows studying the behavior of systems, real or not, in various conditions, allowing hypotheses to be tested without physical and financial resources are used. In the case of the animal feed industry, this technique becomes a very important tool, especially in the short term planning which involves the management of the floor operations. The animal feed industry is part of the agribusiness chain, and as such, has its inputs internationally listed, commodities, thus effectively managing its installed capacity is a strategic advantage for differentiation before the market needs in terms of cost, time and quality. In this sense, the objective of this study was to develop a discrete simulation model to assist the decision-making process on increasing the rate of bagging an animal feed industry, located in the state of São Paulo. For this study it has been used the Arena® software, Rockwell Software, and as a method of research modeling and simulation, and the simulation model development stages followed the methodology proposed by Law and Kelton (2000) and Banks (2010). Data were always collected with the same operator at the same time. As a result of simulation of the proposed model was possible to analyze different scenarios, assessing the dynamics of the system and with the performance indicators the equipment utilization rate, the amount of products produced and the consumption of electricity and natural gas per ton of product produced. Whereas the use of discrete simulation in animal feed industry belonging to the process industry and with hybrid production process, could be used due to the approach proposed by Spieckmann and Stobbe (2012). / A busca pelo aumento de produtividade tornou-se um mantra repetido à exaustão em muitas empresas imersas em um mercado globalizado. Neste contexto, muitas técnicas computacionais vêm ganhando espaço, conquistando adeptos, auxiliando e refinando o processo de tomada de decisão. Dentre as várias técnicas disponíveis, a simulação discreta se destaca, pois permite estudar o comportamento de sistemas, reais ou não, sob diversas condições, possibilitando que hipóteses sejam testadas sem que recursos físicos e financeiros sejam utilizados. No caso da indústria de nutrição animal, essa técnica se torna uma ferramenta muito relevante, principalmente no planejamento de curto prazo que envolve a gestão das operações do chão de fábrica. A indústria de nutrição animal está inserida na cadeia do agronegócio, e como tal, tem seus insumos cotados internacionalmente, commodities, assim uma gestão eficaz de sua capacidade instalada representa uma vantagem estratégica de diferenciação perante as necessidades do mercado em relação a custo, prazo e qualidade. Neste sentido, o objetivo deste trabalho foi desenvolver um modelo de simulação discreta para auxiliar o processo de tomada de decisão sobre o aumento da taxa de ensaque de uma indústria de nutrição animal, localizada no interior do estado de São Paulo. Para a realização deste estudo foi utilizado o software Arena®, da Rockwell Softwares, e como método de pesquisa a modelagem e simulação, sendo que as etapas de desenvolvimento do modelo de simulação seguiram a metodologia proposta por Law e Kelton (2000) e Banks (2010). Os dados foram coletados sempre com os mesmos operadores no mesmo horário. Como resultado da simulação do modelo proposto foi possível analisar diferentes cenários, avaliando a dinâmica do sistema e tendo como indicadores de desempenho a taxa de utilização dos equipamentos, a quantidade de produtos produzidos e o consumo de energia elétrica e gás natural por tonelada de produto produzido. Sendo que a utilização da simulação discreta na indústria de nutrição animal, pertencente à indústria de processo e com processo produtivo híbrido, foi possível devido à abordagem utilizada, proposta por Spieckmann e Stobbe (2012).

Småskaliga processindustrier är små industrier som genom ett småskaligt, hantverksmässigt eller lokalt förhållningssätt förädlar råvaror genom olika automatiserade processer. Vid förädlingen uppkommer stora mängder processavloppsvatten med stor organisk belastning som måste tas om hand på ett hållbart, resurseffektivt och miljömässigt sätt för att inte skada människa eller miljö. I denna studie undersöktes kvaliteten på processavloppsvatten från småskaliga slakterier, mejerier och bryggerier, samt hur hanteringen av processavloppsvattnet från dessa processindustrier ser ut i Sverige idag. Ytterligare utreddes hur reningstekniker för små avlopp kan användas för rening av processavloppsvatten från småskalig processindustri samt hur marknaden för användande av tekniker för små avlopp för rening av processavloppsvatten ser ut. Studien använde ett flertal metoder, litteraturstudie av småskaliga processindustrier och små avlopp, intervjuer och enkätundersökning av småskaliga slakterier, mejerier och bryggerier, samt intervjuer med tillverkare för tekniker för små avlopp. Resultatet visade att kvaliteten på processavloppsvattnet inte kunde redovisas för majoriteten av processindustrierna från intervjuer och enkätundersökning eftersom kvalitetsanalyser inte alltid verkar ske på processavloppsvattnet, varken före eller efter rening. Litteraturen beskrev vidare att prioriterade parametrar att rena för slakterier, mejerier och bryggerier främst är organiska ämnen (mätt som BOD eller COD), suspenderade ämnen, kväve, fosfor, samt pH. Dessa parametrar varierar mellan de olika typerna av processindustrierna och inom samma typ av processindustri. Variationerna anses utgöra en utmaning att hitta passande reningstekniker som fungerar i alla sammanhang. Angående vilka reningstekniker och avloppslösningar som används av småskaliga processindustrier visade resultatet att en stor andel av processindustrierna har intern rening, och knappt en tredjedel har anslutning till kommunalt avloppsnät. Processindustrier med intern rening vars processavloppsvatten dimensionerades till mindre än 100 personekvivalenter använder till övervägande del tekniker för rening av små avlopp, men andra avloppslösningar såsom gödselbrunn, reningsverk och biogasanläggning förekom även för större avloppsdimensioner. Reningstekniker för små avlopp för rening av processavloppsvatten, samt anpassade tekniker för processavloppsvatten, erbjuds till viss grad på dagens marknad men det finns fortfarande utmaningar för att kunna tillhandahålla lösningar för fler typer av processindustrier. Möjlighet att utjämna avloppsflöden och lösningar med större belastningskapacitet är fortfarande något som behöver utvecklas vidare. / Small-scale process industries are small, sometimes locally or artisanal, industries that produces their product through processing raw materials by using automated processes. Large volumes of wastewater effluent are produced by doing this, and this wastewater is characterized by high organic load and nutrients which must be treated in a sustainable way to not be harmful to humans nor the environment. This study evaluated industrial wastewater treatment from small-scale slaughterhouses, dairies and breweries, including wastewater characteristics of these types of process industries in Sweden today. The study also included an evaluation of decentralized wastewater treatment systems for small-scale industrial wastewater treatment and what the Swedish market can provide regarding small-scale industrial wastewater treatments. Different methods were used to reach this goal; a literature study regarding wastewater characteristics and treatment of industrial wastewater and decentralized wastewater treatment systems, interviews, and surveys of Swedish small-scale process industries, and finally interviews with manufacturers of decentralized wastewater treatment systems. The result showed that wastewater characteristics was not accessible from most of the Swedish small-scale process industries. They mostly do not analyze their wastewater neither before nor after wastewater treatment. Furthermore, it was described that highpriority wastewater characteristics for treatment according to the literature was BOD, COD, suspended solids, nitrogen, phosphorus, and pH. Variations of these characteristics is common both between different types of process industries and in the same type of industry. These variations are challenging in regard to finding suitable wastewater treatment techniques that is adequate in every situation. Wastewater treatment systems used today are mostly local at the site, it is around a third that have connection to municipal wastewater facilities. The most common local wastewater treatment for small process industries (less than 100 population equivalents) is decentralized wastewater treatment systems according to the interviews and surveys. Other wastewater treatments such as dung pits, wastewater treatment plants and biogas plants were also used for larger process industries. Decentralized wastewater treatment systems for industrial wastewater treatment and adapted small-scale industrial wastewater treatments can be found to some extent on the Swedish market today, but there are still some challenges to provide small-scale industrial wastewater treatment for every type of process industry. Solutions to level out intense wastewater flows and capacity to receive high effluent loads need to be further developed.

Process monitoring is a field that can greatly benefit from the adoption of machine learning solutions like recommendation systems. However, for domain experts to embrace these technologies within their work processes, clear explanations are crucial. Therefore, it is important to adopt user-centred methods for designing more transparent recommendation systems. This study explores this topic through a case study in the pulp and paper industry. By employing a user-centred and design-first adaptation of the question-driven design process, this study aims to uncover the explanation needs and requirements of industry experts, as well as formulate design visions and recommendations for transparent recommendation systems. The results of the study reveal five common explanation types that are valuable for domain experts while also highlighting limitations in previous studies on explanation types. Additionally, nine requirements are identified and utilised in the creation of a prototype, which domain experts evaluate. The evaluation process leads to the development of several design recommendations that can assist HCI researchers and designers in creating effective, transparent recommendation systems. Overall, this research contributes to the field of HCI by enhancing the understanding of transparent recommendation systems from a user-centred perspective.

Background: The Digital Twin is an increasingly trending technology that utilizes many of the key technologies relevant to the digitalization of industries and Industry 4.0, such as AI, Big Data, and IoT, to bring a virtual asset and a physical asset together to perform analysis and execute real-time decision making backed up by data (Grieves & Vickers, 2017; Rasheed et al., 2020). Current research on the benefits and challenges of Digital Twins in process industries is sparse and under-developed, and the significance of Digital Twins in their operational lifecycle phase requires investigation (Perno et al., 2020; Schleich et al., 2019; Sjödin, 2013). Research Questions: RQ1: What are the benefits of industrial process plant Digital Twins for companies in process industries? RQ2: What are the challenges that companies will face with industrial process plant Digital Twins in process industries? Literature Review: A theoretical framework was developed based on the applications, challenges, and enablers researched in other industries which acted as a foundation for the data collection process. Research Method: The thesis follows a qualitative research approach. A single-case study was employed with a large equipment supplier in the mineral processing industry, where data was collected through 17 semi-structured interviews with people possessing in-depth knowledge about the needs of the mineral processing industry. Findings: Five main benefits of industrial process plant Digital Twins in process industries were identified, Process performance, Monitoring and control, Predictive maintenance and scheduling, Business opportunities, and Safety. Correspondingly, four main challenges were identified, Perception and presentation, Privacy and security, Data management and performance, and Mutual scope and focus. Conclusions: The thesis project's managerial and theoretical implications include providing equipment suppliers in process industries with what benefits there lie with industrial process plant Digital Twins and which challenges must be overcome. By providing these benefits and challenges to equipment suppliers, they can prioritize which of these are most important to consider in their situation. The thesis contributes to the research of Digital Twins and adds to the sparse existing knowledge of what the benefits and challenges are of industrial process plant Digital Twins in process industries. The main limitation is the absence of process plant companies during the data collection phase.

The purpose of this dissertation is to propose a framework for sales and operations planning (S&OP), which is based on a modularized view of supply chains. The framework should support both process industries and discrete manufacturing industries in their quest for performance. S&OP has been highlighted in this framework due to its essential role in integrating different functions within a company and integrating a company with its supply chain partners (referred to as horizontal integration), and linking different planning levels in a company (referred to as vertical integration). As an integrator, S&ÖP influences companies’ performance. Originally, S&OP was developed as a generic process but still in line with the requirements of discrete manufacturing industries. The specific requirements of process industries have not been emphasized in this process to the same extent. In order to suggest a modularized S&OP framework for both process industries and  discrete manufacturing  industries, a systematic literature review is performed to understand the specific characteristics of S&OP in process industries. As a result, the importance of continuity/discontinuity of materials and its influence on the required production processes are highlighted. This indicates that the production process in process industries is actually a hybrid of continuous production and discrete production, whereas the discrete manufacturing industries often only deploy discrete production. Continuous production has specific characteristics that would be beneficial to include in the S&OP process; nonetheless, this is in contrast to the view in the literature that considers S&OP a generic process. Generic here means that S&OP is independent of the context in terms of, for example, the industry in which it is implemented. This issue is investigated in this dissertation by identifying the requirements, which can be considered in the S&OP of process industries as add-ons to the generic S&OP. In addition to this, two other concepts addressing the properties of the production process are identified as important in planning and control, including S&OP. One addresses the level of repetitivity of the production process in response to the market demand, and the other concerns the trigger of the production flow. The three concepts are related to three different types of decoupling points and are the basis for a typology developed herein that provides a modularized view of supply chains. The application of the typology to S&OP leads to a modularized S&OP framework applicable to both process industries and discrete manufacturing industries. The modularized view of supply chains has been long emphasized as an effective and efficient way to support companies’ performance and their competitive position. The typology and the S&OP framework are developed through conceptual research methods. To study how the modularized S&ÖP framework is related to companies’ performance measures, different performance measures (including sustainable performance measures) at the S&OP level are extracted from the literature. The performance measures are then classified according to the typology, and linked to strategic performance attributes. Aligning performance measures at S&OP levels and strategic performance attributes would help in enhancing companies’ performance. Sustainable performance measures are included in this classification to provide additional support for companies’ performance. Finally, this approach in classification of  performance measures is studied in four case companies, and the empirical performance measures are linked to the companies’ strategic performance attributes and competitive strategies. The results of this empirical study have, to some extent, verified the results from the classification of performance measures based on the literature. This dissertation contributes to the development of knowledge in S&OP. First, it identifies three key concepts in planning and control of manufacturing companies. Second, it investigates how S&OP should be tailored to the specific characteristics of companies and their supply chains. The modularized S&OP framework developed in this dissertation is based on the three identified concepts. This framework provides a foundation for fulfilling the supply chains needs by suggesting decision-making processes, planning techniques, and performance measures for different modules. More specifically, this work investigates how S&OP should be designed and implemented in process industries, which has not been extensively studied before. Third, this dissertation shows how S&OP level performance measures can be selected in line with the specific characteristics of supply chains. Finally, by integrating the sustainable performance measures in the S&OP process, this dissertation expands the scope of S&OP and its potential in supporting companies’ performance.

The ever increasing diversity in communication systems has created a demand for constant improvements in receiver components. This thesis describes the design and characterisation of front-end receiver components for various challenging applications, including characterisation of low noise foundry processes, LNA design and multi-band antenna design. It also includes a new theoretical analysis of noise coupling in low noise phased array receivers.In LNA design much depends on the choice of the optimum active devices. A comprehensive survey of the performance of low noise transistors is therefore extremely beneficial. To this end a comparison of the DC, small-signal and noise behaviours of 10 state-of-the-art GaAs and InP based pHEMT and mHEMT low noise processes has been carried out. Their suitability in LNA designs has been determined, with emphasis on the SKA project. This work is part of the first known detailed investigation of this kind. Results indicate the superiority of mature GaAs-based pHEMT processes, and highlight problems associated with the studied mHEMT processes. Two of the more promising processes have then been used to design C-band and UHF-band MMIC LNAs. A new theoretical analysis of coupled noise between antenna elements of a low noise phased array receiver has been carried out. Results of the noise wave analysis, based on fundamental principles of noisy networks, suggest that the coupled noise contribution to system noise temperatures should be smaller than had previously been suggested for systems like the SKA. The principles are applicable to any phased array receiver. Finally, a multi-band antenna has been designed and fabricated for a severe operating environment, covering the three extremely crowded frequency bands, the 2.1 GHz UMTS, the 2.4 GHz ISM and the 5.8 GHz ISM bands. Measurements have demonstrated excellent performance, exceeding that of equivalent commercial antennas aimed at similar applications.