Teresa Ângela

Rochetti

Renato De Campos

A Comparative Analysis Between BPMN and ISO 19440 Modeling Language Constructs

Keywords: Process modeling, Enterprise, Modeling, BPMN, ISO 19440

Enterprise modeling is a tool that can be used for simple objectives, such as understanding how a part of the enterprise works, to more complex objectives, such as information flow for the computerized systems, or knowledge storage in an organization. There are several languages proposed for enterprise modeling, such as BPMN, CIMOSA and UML. They have different characteristics, advantages and disadvantages. This paper presents a comparison in relation to representation capacity between the ISO 19440 language constructs and the BPMN notation based on their constructors and icons. The analysis shows that BPMN has less representation capacity, showing differences between one language for modeling various aspects in an enterprise (ISO 19440) and a notation (BPMN) which focuses on process modeling and has few constructs for representing other aspects such as an enterprise's resources and organization..

Introduction

For business enterprise be understood and integrated, it is necessary for them to be systematically represented as models [START_REF] Kalpic | Business Process Modelling in Industry-the Powerful Tool in Enterprise Management[END_REF]. They differs in the number of details according to the perspective of the person, where each person will naturally have a slight difference in the point of view of enterprise objectives and visions [START_REF] Eriksson | Business Modeling With UML: Business Patterns at Work[END_REF][START_REF] Doebeli | Using BPM Governance to Align Systems and Practice[END_REF]. Enterprise modeling languages define generic modeling constructors for enterprise modeling adapted to the needs of people who create and use enterprise models [START_REF] Force | GERAM: Generalised Enterprise Reference Architecture and Methodology[END_REF]. There are several languages and notations for enterprise modeling, such as BPMN, UML and CIMOSA, among others [START_REF] Mertins | Architectures, Methods and Tools for Enterprise Engineering[END_REF][START_REF] Minoli | Enterprise Architecture A to Z: Frameworks, Business Process Modeling, SOA, and Infrastructure Technology[END_REF][START_REF] Vernadat | Enterprise Modeling and Integration, Principles and Applications[END_REF]. ISO 19440 defines a generic set of language constructs for enterprise modeling with common semantics, capable of unifying models developed by different people at various stages of development of business models, which support decision-making, monitoring and control. New proposals have emerged aimed at enterprise business modeling and management [START_REF] Mccormack | A Global Investigation of Key Turning Points in Business Process Maturity[END_REF][START_REF] Palmberg | Experiences of Implementing Process Management: A Multiple-case Study[END_REF]. Business Process Management (BPM) is gaining force, which is normally supported by use of modeling tools based on Business Process Modeling Notation (BPMN) [START_REF] Kohlbacher | The Effects of Process Orientation: A Literature Review[END_REF]. Since several alternative proposals exists, it becomes important to know the characteristics, advantages, disadvantages and representation capacities of each for appropriate use.

This paper presents a comparison between ISO 19440 language constructors and BPMN notation. Thus, below we give a brief description of ISO 19440 constructs and BPMN. Then, a comparative analysis is presented and final considerations.

ISO 19440 Modeling Constructs

The standard ISO 19440 supports enterprise modeling, and was created based on developments of modeling techniques as CIMOSA, GRAI, GERAM, among others [START_REF] Carnaghan | Business Process Modeling Approaches in the Context of Process Level Audit Risk Assessment: An Analysis and Comparison[END_REF]. His last update was in 2007, and was prepared by the European Committee for Normalization (CEN), Technical Committee CEN / TC 310, in collaboration with Technical Committee ISO / TC 184 (Integration and Industrial Automation Systems), Subcommittee SC 5 (Architecture and Structures Integration and Communication). They were also received contributions from members of the Task Force on Enterprise Integration IFAC / IFIP, the consortium CIMOSA, and the European project ATHENA [START_REF]International Organization for Standardization[END_REF]. ISO 19440 defines generic constructors to a modeling language based on enterprise business processes, described on templates. These constructs include generic attributes predefined in this standard, however, other attributes can be added for a particular need. They can be categorized according to their main views:

-Function and process-related: Domain, Business Process, Enterprise Activity, Event, Functional Operation, and Behavioral Rules; -Information-related: Enterprise Object, Enterprise Object View, Order, Product; -Resource-related: Capability, Operational Role, Resource, and Functional Entity; -Organization-related: Person Profile, Organizational Role, Organization Unit, and Decision Centre.

These constructs are described below, based on the standard itself [START_REF]International Organization for Standardization[END_REF]:

-Domain: Represents the boundary and the content of an enterprise or a portion of an enterprise for which an enterprise model is to be created. -Business Process: Represents all or part of the domain functionalities, its internal structure and its dynamic behavior. A Business Process construct shall describe the functionalities needed to produce a desired result that satisfies business objectives. -Behavioral Rules: The purpose of the behavioral rules is to identify the start of the main Business Process, and describe the logical sequencing relationships of constituent Business Processes or Enterprise Activities, or both. -Enterprise Activity: Represents the part of process functionality that is needed to realize a basic task within a Business Process. They are the lowest level constituents of a Business Process defined according to required user objectives for control.

-Functional Operation: Represents a part of the functionality of an Enterprise Activity, which has been decomposed into a number of transformation functions.

-Event: The purpose of the Event construct is to capture reason, origin and destination of an event. An Event shall represent the initiation of a state change in the enterprise or its environment, to be used to initiate the execution of one or more processes. -Enterprise Object: Describe those characteristics (attributes and relational structure) and to provide for selection of relevant parts (Object Views) that are to be identified in the modeling process and used during the operational phase.

-Enterprise Object View: The purpose is to enable the identification of relevant attributes from a particular Enterprise Object as required by a Domain, a Business Process, or an Enterprise Activity for the definition of their inputs and outputs. It shall represent a subset of the descriptive attributes of an Enterprise Object.

-Product: This construct describes all intermediate stages of product life cycles with regard to both material and informational aspects. It is a very important construct because fabrication and sale of products are the aim of the enterprise. -Order: Order construct describes what has to be done, which products are to be produced, which resources are to be used, and what purchases have to be made. -Resource: The purpose of the Resource construct is to classify and describe in terms of capabilities all material and informational aids in an enterprise, such as machining equipment, tools and facilities, documents and files containing geometrical, material and informational characteristics, related the execution of Enterprise Activities. -Capability: Represents the elements of both the capabilities required by an Enterprise Activity and those provided by a resource. -Functional Entity: Describe the Operational Roles and Capabilities provided by the Functional Entity as well as the set of functional operations that can be assigned to it and which it can execute in a quasi-autonomous mode. -Person Profile: Describe the human skill profiles available to serve the assigned organizational and operational tasks and to fulfill the responsibilities associated. Organizational Unit: This construct describes an identifiable entity together with its position relative to other such entities in the enterprise organizational structure. -Decision Centre: The purpose of the Decision Centre construct is to describe its contents (in terms of classes of decisional functions) and its relations to other Decision Centers (the related decisional and information flow) and to Organizational Units. -Organizational Role: Describes the skill profile required to serve organizational responsibilities and to fulfill those responsibilities. A skill profile shall be a list of predefined or user-defined human organizational skills, described in terms appropriate to the user of those skills and understandable by the person providing them. -Operational Role: Skill profile required and provided to undertake the defined operational tasks. It shall be a list of predefined or user-defined human operational skills, described to the user of those skills and understandable to the person.

3 Business Process Management Notation (BPMN)

Business Process Management (BPM) gathers business management and information technology promoting the integration and improvement of the organizations' business processes using methods, techniques and tools to model, publish, control and analyze operational processes involving diverse people and systems. BPM's objectives are typically [START_REF] Minoli | Enterprise Architecture A to Z: Frameworks, Business Process Modeling, SOA, and Infrastructure Technology[END_REF]: obtain knowledge about the enterprise's business processes; use this knowledge of business processes in the reengineering project of business processes to optimize the operation; facilitate enterprise decision making; support the interoperability of business processes. In the context of BPM, one of the main characteristics is the Business Process Management System (BPMS) modeling tools, which usually adopt Business Process Modeling Notation (BPMN). The latter refers to a series of standard icons for designing processes, which facilitates user understanding [START_REF]ABPMP: Guide to the Business Process Management Common Body of Knowledge[END_REF]. BPMN's main objectives are to standardize business process modeling, expand modeling resources and create a formal mapping between high-level modeling and execution languages. BPMN create a simple mechanism to develop business process models while also ensuring the inherent complexity of the processes. This notation was developed by the Business Process Management Initiative (BPMI) in May 2004, and in June 2005, BPMI merged with the Object Management Group (OMG). In February 2006, OMG adopted and officially published version 1.0 [14].

One of BPMN's major benefits is the reuse of code, because, according to the author, when enterprises construct models of components that represent a specific implementation, they can be stored in model libraries that can be used in the future by another similar application by just importing the model's code [START_REF] Minoli | Enterprise Architecture A to Z: Frameworks, Business Process Modeling, SOA, and Infrastructure Technology[END_REF]. BPMN provides a basic set of diagrams to represent business processes in a simple manner, but that at the same time are capable of controlling the inherent complexity of the business processes. This basic set is divided into four categories [14]: Connection Objects (Fig. 1); Flow Objects (Fig. 2); Swimlanes (Fig. 3); Artifacts (Fig. 4).

Comparisons Between ISO 19440 and BPMN

Procedures for Analyses and Comparisons

After introducing the ISO 19440 language and BPMN notation, a comparative analysis is conducted. The analysis is conducted as per functional, information, resource and organization views. The synthesis of these comparisons is shown in Fig. 5, and the respective discussions and analyses are shown in sequence. It is understood that class objects in ISO 19440 and icons in BPMN are constructors of the respective languages. The classification used in the comparison between modeling language constructors (and their construction elements) was conducted in accordance with the 'correspondence' between constructors. The analysis is made in relation to how much a specific constructor conceptually representing an object or typical entity of an enterprise in a language corresponds to a constructor in the other language (or notation). These correspondences are classified as:

-Strong, for when constructors are conceptually very similar, corresponding to the representation of the same object or entity in a model, admitting a few minor and insignificant differences in this representation; -Average, for when constructors are conceptually similar, corresponding to the representation of the same object or entity, however with significant differences in representation of the same concept, for example, in the case of constructors that have a large number of elements of different information (or attributes); -Weak, for when constructors are conceptually little similar, not exactly representing the same object, but having aspects related to the objects being represented.

When a language does not have a constructor representing some aspect of a constructor of another language, the relative space in the box is kept blank.

Analyses and Comparisons

The framework of Fig. 5 shows the name of the languages being compared and the respective classifications of correspondences, followed by analyses and observations. For Business Process, Event, Enterprise Activity and Functional Operation, constructors of ISO 19440, it was identified strong correspondences (very similar) in BPMN.

The Business Process constructors in ISO 19440 can be represented in BPMN by the Sub-Process constructor, a specific case of Activity.

The Domain construct in ISO 19440 could be represented in a weak similar manner with Group notation, grouping a certain number of processes from an enterprise's functional area in the model (which could be a department or not).

The Domain Relationship could be represented by a set of Events, Messages or Data Object. The ISO 19440 Behavior Rule construction element can be represented by the combination of Events and Flows in BPMN, being considered of average correspondence (similar). Although it is possible to conceptually represent the same object (behavior rules for processes) with these symbols, behavior rules in ISO 19440 have greater flexibility in representation in terms of logical expressions and are not restricted to BPMN's graphic representations.

Information view constructors in ISO 19440 has correspondence average (little similar) with Artifacts in BPMN, being more similar to Data Objects. In BPMN, an artifact represents a datum, however, without interfering in the flow.

Weak correspondences were also considered between ISO 19440's Organization unit constructors and Pool and Lane element (since it is a sub-division in BPMN), and between ISO 19440's Decision Centre and the Lane element (which be used as a container to separate a decision activities). Then, BPMN symbols represent few aspects related to organization.

In the comparisons between ISO 19440 and the BPMN language, a synthesis analysis show that four of six ISO 19440's constructors in the Function View have a strong correspondence in BPMN, and two have average correspondence. For the Information View, the constructors have average correspondence. The ISO Since BPMN focuses on processes, it would be expected for this notation to be fitting for process modeling (functional and business related aspects). Thus, from the comparisons, it can be perceived that it minimally represents some aspects of the information and organization views, and that it does not explicitly represent aspects of the resources view.

Final Considerations

This paper presented a comparison in relation to representation capacity between the ISO 19440 language and the BPMN notation based on their constructors. The analysis shows that BPMN has less representation capacity, showing differences between one language for modeling various aspects in an enterprise (ISO 19440) and a notation (BPMN) which focuses on process modeling and has few constructs for representing other aspects such as an enterprise's resources and organization.

In BPMN notation, the basis for representing enterprise aspects is the graphic elements. Although BPMN has a significant number of graphic symbols, these constructors do not present detailed templates, like ISO 19440.

Although ISO 19440 defines a larger and much richer set of modeling constructors, on the other hand, a standard for the graphic representation of its main constructors is lacking. The graphic representation could provide a first understanding of the model, and then moving on to an understanding of details using templates that refer to its classes of objects and description elements (properties). The procedure used for analyses and comparisons employs a certain degree of subjectivity, and if more detailed comparisons are wanted, another technique must be used. However, the comparison and analysis in this paper will help users or analysts identify some gaps and correspondences that eventually permit discarding or classifying the languages in relation to some modeling objective, or for needs in terms of some specific view (functional, information, resources or organization), or a specific level of detail.

Fig. 1 .Fig. 2 .Fig. 3 .Fig. 4 .

 1234 Fig. 1. Connection Objects. (Source: Adapted from BPMI [14])

Fig. 5 .

 5 Fig. 5. Comparison between ISO 19440 and BPMN constructors


Átila Melo De Lira

Herbert Gonc ¸alves Espuny

Pedro Luiz De Oliveira

Costa Neto

Reinaldo De

Ara Újo Lopes

Health Tourism as an Inducer of Economic and Social Development in Teresina City

Keywords: Tourism, Health pole, Sustainable development

In recent years, the global growth of the economy contributed to the significant increase of tourism in the world, spreading its concepts in Brazil. There have also grown the related researches in the academic sector, as well as its concern with long life companies, growth in the Northeast region, globalization and other changes occurring in the short term. Thus, this work aims to present how a state among those with lower income per capita in the Federation, as Piauí, has a health care system in its capital which is a benchmark in Northeastern Brazil, influencing positively health tourism. The work deals with issues involving tourism as a product and service, having as a result the existence of a cluster of health in the city of Teresina with economic expression that justifies its importance as a generator of income, employment, science and technology and a promoter of sustainable development in that city.

Introduction

According to the World Tourism Organization [START_REF] Organizac | Conselho de Turismo e Neg ócios da Fecomercio[END_REF], tourism receipts reach US$ 919 billion. There was a slowdown in the tourism sector due to the global economic crisis of 2008, which caused some instability in the confidence of agents for future events. However, despite the crisis, to make a comparative analysis of ten years prior to 2010, the foreign exchange earnings from tourism in 2008 (US$ 857.40 billion) was 92.67% higher than in 1999 (US$ 445,00 billion), demonstrating a significant growth in a decade. Also according to the UNWTO [START_REF] Organizac | Conselho de Turismo e Neg ócios da Fecomercio[END_REF], between 1999 and 2010, the international flow of tourism in the world grew by 49%, beating the mark of 935 million trips in 2010, an estimated 1.6 billion in 2020. The Figure 1 illustrates the growth of the sector during the period.

The UNWTO researches of 2010 also present important data of the tourism sector in Brazil, indicating that in the same period the foreign exchange earnings more than tripled from US$ 1.81 billion in 1999 to US$ 5.92 billion in 2010.

Fig. 1: Growth of the tourism sector (Source: [START_REF] Organizac | Conselho de Turismo e Neg ócios da Fecomercio[END_REF])

Contextualizing the city of Teresina, in this article, with about 850,000 inhabitants, Piauí state capital, Brazil, Northeast, one of the poorest in the country, but whose capital emerged as a respectable health pole with qualified service as a result of the entrepreneurial spirit of its main managers. The Health Pole of Teresina (PI) has shown strong growth in recent years, becoming a regional referral center. A first diagnosis made by Piaui Hospitals' Union shows that 30% of clients served come from six other states of the federation, generating jobs and income for the city [START_REF]Agenda 2015 da Prefeitura de Teresina[END_REF].

The beginning of the development of a health cluster, with the formation of a supply chain and connected services, bringing benefits in terms of cost reduction, quality improvement, training of skilled labor, capital attraction and generation of employment and income. This benefit extends to the Health Private Network, increasing their participation in services to the population through an investment which reached US$ 68 million reais in 2011, according to the Medical Union of Piaui

The central objective of this article is to demonstrate the contribution of health tourism as an encouraging instrument for the beginning and the growth of companies as well as a mechanism that contributes to the company to assume more effectively its social function, contributing to improving the quality of life of a particular region and also as immediate growthinducing factor of Teresina.

Definition of Tourism and its Classifications

Tourism can be focused as a phenomenon that refers to the movement of people within their own country (domestic tourism) or crossing national borders (international tourism). This movement reveals elements such as interactions and individual or team relationships, human understanding, feelings, perceptions, motivations, pressures, satisfaction, the concept of pleasure, etc [START_REF] Wahab | Introduc ¸ão à Administrac ¸ão do Turismo[END_REF].

According to Castelli [START_REF] Castelli | Hospitalidade: A Inovac ¸ão na Gestão nas Organizac ¸ões Prestadoras de Servic ¸os[END_REF], the comprehension of the phenomenon of tourism current must necessarily pass through an analysis of the meaning of the trips in the course of history. These, frequently, were moved by economic political and military interests. Nowadays, travels with these same objectives continue to move people from one region to another.

Travelling is an action arising from a context which is inserted into the society at a specific moment in history. It has always been one of the elements of economic and social life and, especially, of the world which is inserted. To each type of civilization or society corresponds a way to travel or accept the traveler.

As stated by Wahab [START_REF] Wahab | Introduc ¸ão à Administrac ¸ão do Turismo[END_REF], the anatomy of the phenomenon of tourism would be basically composed of three elements: the man (human element as the author of the act of tourism), the space (physical element, covered by the act itself), and time (temporal element that is consumed by the journey itself and by staying at the destination). These elements are representative of the conditions of this phenomenon existence.

However, other factors distinguish tourism from the simple act of traveling. Such factors relate mainly to the goals, the temporary nature of displacement, the use of tourist services and equipment and, what would be the most important among them, the concept of pleasure and recreation as fundamental.

Olimpio [START_REF] Olimpio | Introduc ¸ão ao Estudo do Turismo[END_REF] affirms that a revolution in the traditional concepts of trips was performed by the tourism phenomenon from the middle of the nineteenth century when the Protestant Pastor Thomas Cook inaugurated the first tourist agency in England.

Countries such as Italy, France and Spain, old military powers and colonialists, managed to stabilize their balances of payments in the postwar due to tourism, reaching to the point of this activity is to constitute real industry, with its own public body, specific legislation, which aims to regulate the various aspects of social, economic, commercial and cultural tourism, always aiming at better income and greater expansion of the tourist industry.

Factors that Influence Tourist Decisions

Every person is a tourist in potential, being necessary, however, the action of the tourist trip to characterize as so. For this reason there are some constraints as: the desire (animus) and the possibility [START_REF] Olimpio | Introduc ¸ão ao Estudo do Turismo[END_REF]. The desire can originate from different causes such as: propaganda, the status, habit, physical convenience, moral or intellectual, seduction, commercial interest or of profit and health. The second constraint involves factors that are beyond the control of man, as: time vacant, money, means of transport, among others.

As the possibility was always easier to exist in the most privileged classes, the concept of tourism is usually bound by luxury. However, with paid vacations, social tourism became easier and popular.

In this way, there are various reasons that people become tourist: business, religious reasons, health, culture, education and pleasure are just a few examples.

According to Arrillaga [START_REF] Arrilaga | Introduc ¸ão ao Estudo do Turismo[END_REF], the needs that tourism satisfy can be very varied, since the subjective causes that determine the tourist trips are as diverse as the needs which the body or the human soul may experience.

The tourist motivations or subjective causes of tourism can be classified into primary and secondary; direct and indirect; proximate and remote; individual and social.

However, the tourist deciding to travel generally has more than one cause, as shown below.

-Primary and Secondary causes. For example, a person who performs a pilgrimage has, as main cause, the obtaining of a grace of the spiritual order, however, also weighs in its decision the possibility to get to new places, visit the famous monuments, rest, among others. -Direct and indirect causes. The achievement of a certain journey may occur due to an invitation or the desire to know some locality. However, it can involve indirect causes, such as the habit of travel or the socioeconomic level of the traveler. -Proximate and remote causes. As an example of proximate cause of a trip, is the propaganda of a travel agent and as remote cause example, the remembrance of a previous trip. -Individual and social causes. The Individual Causes act in the decision of a person to travel and the Social Causes influence by equal in sectors of the population. As an example of the first, we can mention the practice of a sport and of the second, the fashion or ideological affinities. The particular motivation for health tourism allows to consider it due to primary, direct, proximate and individual causes.

Tourism Classifications

According to a first general classification according to Andrade [START_REF] Andrade | Turismo: Fundamentos e Dimensões[END_REF], the city of Teresina case and its health pole may be classified as a regional receptive nucleus of people for health treatment, and internal, because the temporary flow is typically regional in the country itself. The Table 1 exposes in objective way the more common tourism types. Is the set of activities of travel, accommodation, food and leisure activities practiced by travelers relating both to commercial and industrial activities; Active sports Refer to all the activities of travel with an objective to participate in sporting events, in the country or abroad; Health Also known as therapeutic tourism or treatment, refers to the set of tourist activities to acquire good physical and mental health; Religious Set of activities that involve visits to the receptive that express mystics feelings or raise the faith, hope and charity to believers;

For purpose of this work we will use the typology of health tourism, because that is what happens in some health poles regional throughout Brazil as, for example, the focus of this paper, the case of Teresina. Table 2 Refers to the hosting and the set of activities in a same core, with duration of at least three weeks. This method excludes the tours and excursions to other receptive; Itinerante Involves a series of lodging in different places, consists of visits to the greatest possible number of receptive cores, on a single trip, with short stay in the visited places.

According to the form, you can classify the people who migrate to Teresina for health treatment in individual, because most of the time travelers get to the city with its own resources by regional and interstate bus that cut the city through the various highways in the state.

Tourism Industry

The internal relationship that exists between tourism and the economic science is always expressed in terms of the contribution of tourism to economic development. Wahab [START_REF] Wahab | Introduc ¸ão à Administrac ¸ão do Turismo[END_REF] writes that: "Tourism is a phenomenon that involves the transfer of capital from one country to another through the movement of tourists who go to certain touristic"product" and consume. They are potential consumers of complex goods and services that are offered with a specific goal. The tourism, through the aspects of consumption and investment, affects different sectors of the economic system of a country, and it is believed that its multiplier effect is higher than that observed in other sectors of the economy such as industry. .. "

.

Tourism is productive, accurate and determined with specific characteristics, joined to the field of development and commerce. So, depending on the stage of development of a country or a region, it can be considered the first force, ahead of industry and agriculture.

According to data from the Brazilian Tourism Company -Embratur [START_REF] Baptista | Caderno temáticos da Embratur[END_REF], the tourist industry in recent decades has shown representative economic value. This fact is evidenced by the volume of transactions carried out as a result of increased demand for travel and tourism.

The following part of this paper, will discuss some economic concepts that are directly linked to the tourism industry of the real economy of a region.

Economic Concepts

Some economic concepts that influence the study of tourism as an industry are: economic good, utility, economic agents, tourist product, demand and supply of tourism.

As Lage [START_REF] Lage | Economia do Turismo. Papirus[END_REF] presents, all that is rare and exists in less quantity than needs is an economic good. Thus, because of this lack, something need to be produced, taking the form of goods (materials) or services.

As the consumers cannot get everything they want, they are forced to make choices. Therefore, they may have preference for a given good service but accept a minor amount of another. However, in any situation, consumers act rationally in order to obtain maximum satisfaction from their spending.

Economic and Social Implications of Tourism

As state by Baptista [START_REF] Baptista | Turismo: Gestão Estratégica[END_REF], tourism advantages for a country or a receiving state are:

-Increase of revenues in foreign currency from the sale of goods and services; -Creation of new sources of revenue in various economic sectors; -Low investment compared to the revenue stream that it promotes; -The integration between people of regions, languages, habits and different tastes.

The economic impacts generated by tourism can be classified according to Gunn [START_REF] Lage | Economia do Turismo. Papirus[END_REF] as : direct impact, known as the total income generated in the tourist sector as a direct result of the variation in spending on these products; indirect impact, the total income generated by the spending of the tourism sectors in goods and services offered in the economy, and induced impact, a result of the direct and indirect impacts of tourism, income levels increase throughout the economy, and that part of this additional income will be spent on goods and services produced domestically.

5 The implication of health tourism at Teresina city As a result of these impacts related to health tourism in Piaui capital, it is possible to show in an objective way, that an integrated set of these impacts on the local economy, created 15,000 direct jobs and an annual average investment of 80 million reais (approximately US$ 22 million, values converted to the exchange of 04.05.2016) order of direct and indirectly related to sectors linked with the area in question. The tourism industry has the positive impact on the economy of a city, according to Andrade [START_REF] Andrade | Turismo: Fundamentos e Dimensões[END_REF], by: (i) increased income of the visited place by foreign exchange inflows; (ii) stimulation of investments and creation of new jobs; (iii) the redistribution of wealth between the places of origin and destination.

As negative impacts are mentioned: inflationary pressure, being harmful to the population of the tourist regions, because the high prices in general also affect goods and essential services; high dependence on tourism, making the economy of the region vulnerable to seasonal fluctuations in demand for tourism products; and the social and environmental costs in the tourist areas and residents; So, with these definitions and characteristics of tourism, it is clear the importance and complexity of the tourism for sector in a particular country or region, since it can not only brings capital exchange, but also prosperity to a particular community with regard to professional qualifications, better quality of life with a better performance of the services offered to the population.

Conclusion

Tourism is an industry with multivariate interests. Bringing the tourist to a particular location has different motivations. A developing region, like the Brazilian Northeast, needs to use all possible ways to seek an economic and socially sustainable development that adds value to their economy. The pursuit of excellence in health services, as demonstrated by the Teresina case, is an economic and social way of doing this, especially in regions waiting fordevelopment.

Table 1 :

 1 Tourism types classifications (Source:[START_REF] Andrade | Turismo: Fundamentos e Dimensões[END_REF])

	Classification	Description
	Vacation	Vacation configures a guarantee of an intensive tourism, because the se-
		quence of days available to leisure and rest. It is one of the highest points
		of the profitability of tourism;
	Cultural	Covers the activities for the satisfaction of artistic emotions, scientific,
		training and information in the various existing branches
	Business

Table 2 :

 2 Tourism Form classification (Source:[START_REF] Andrade | Turismo: Fundamentos e Dimensões[END_REF]) organized tourism for people of social layers whose rents, without the help of others, not would allow them to plan a travel. Generally, concerns the vacation colonies of associations, class entities, companies or hostels that work with governmental resources or special funds; Intensive Refers to the set of tourism programs in which people remain hosted in a single location, even if they set tours and excursions to other places; Extensive

	presents a tourism


G Bustamante
email: gustamante1000@hotmail.com

B F Giannetti

F Agostinho

C M V B Almeida

Analysis of the Polyethylene Terephthalate Production Chain: An Approach Based on the Emergy Synthesis

Keywords: Emergy, Specific emergy, Environmental accounting, Petrochemical industry, PET

The petrochemical industry is characterized by the intense use of non-renewable resources, such as crude oil, associated to a high environmental load derived from efforts from nature and human systems to produce these products. These efforts may be accounted for by emergy synthesis, which is a tool that determines the amount of energy, directly or indirectly, necessary to obtain a product or service by means of a common unit (solar equivalent Joules seJ). In this work, emergy synthesis is applied to the polyethylene terephthalate (PET) production chain in the European petrochemical sector. The unit emergy values (UEV) of the system products are estimated, enabling comparative interpretations among the quality of energy usage and processes' efficiency.

Introduction

The importance of the petrochemical industry lies in being a source of large amounts of intermediate products, which are the main raw materials for many other industries like plastic, automotive, transportation, textile and agriculture. However, the production processes with intensive usage of non-renewable natural resources are often associated with high environmental costs, especially in regard to the risk of resource depletion. Therefore, there is an increasing awareness concerning the environmental problems that may arise in the future due to the misuse of strategic non-renewable resources, such as crude oil. In the recent decades, different methods, techniques and research were developed providing knowledge about the specific environmental problems caused by the oil-based production systems. The emergy synthesis, developed by H. T. Odum [START_REF] Odum | Environmental Accounting: Emergy and Environmental Decision Making[END_REF], is an environmental accounting method, based on the laws of thermodynamics and systems ecology, to determine the amount of energy, directly or indirectly, required to produce a good or service. Since the emergy is measured in units of solar equivalent joules (seJ), coefficients called transformities, which represent the emergy intensity through the ratio of emergy (required by the process) to energy (embodied in the product) are used as conversion factors allowing accounting flows are not directly solar origin. The unit emergy values (UEV) refer to the relationship between the quantity of emergy per unit of mass, volume, area, etc., and include the transformities (seJ /J). The UEVs are a measure of energy quality and process efficiency, since the same amount of invested emergy can derive in different types of energy, with different capabilities to produce work and, therefore, different qualities.

Oil-based production systems have been evaluated using the emergy synthesis. Bastianoni et al. [START_REF] Bastianoni | The Solar Transformity of Oil and Petroleum Natural Gas[END_REF] determined the UEVs of oil and natural gas, according to the geological production process and proposed the use of average transformities between the new values and those calculated by Odum [START_REF] Odum | Environmental Accounting: Emergy and Environmental Decision Making[END_REF]. Later, these results were complemented with the estimation of the transformity of liquid petroleum products [START_REF] Bastianoni | The Solar Transformity of Petroleum Fuels[END_REF]. This transformity was used as the emergy contribution of naphtha in a study where different ethylene production processes were evaluated and compared using the emergy synthesis [START_REF] Sha | Solar Energy Footprint of Ethylene Processes[END_REF].

Another method widely used to evaluate the environmental burdens of products and process in petrochemical industry is the Life Cycle Assessment (LCA) [START_REF] Morales | Life Cycle Assessment of Gasoline Production and Use in Chile[END_REF][START_REF] Portha | Estimation of the Environmental Impact of a Petrochemical Process Using Coupled LCA and Exergy Analysis[END_REF]. This method allows estimations of environmental impacts related to different categories, such as global warming, energy use, ozone depletion and abiotic resource use. The complementarity of LCA and emergy synthesis [START_REF] Raugei | Nested Emergy Analyses": Moving Ahead from the Spreadsheet Platform[END_REF] was proposed as an alternative approach, through the application of transformities to the data reported in life cycle inventories (LCI). In spite of the inconsistency issues addressed by Bakshi [START_REF] Bakshi | A thermodynamic Framework for Ecologically Conscious Process Systems Engineering[END_REF] to integrate both approaches, highlighting the differences of the analysis boundaries, the integration of both methods may provide a more comprehensive analysis, including not only the economic and environmental resources required by the production, but also the impact of their emissions [START_REF] Bakshi | A thermodynamic Framework for Ecologically Conscious Process Systems Engineering[END_REF]. LCIs are not conventional data sources for emergy synthesis, but some authors highlighted the accuracy and consistency of results based on this type of information [START_REF] Rugani | Improvements to Emergy Evaluations by Using Life Cycle Assessment[END_REF]. Obstacles, limitations, restrictions and critical points of complementarity or integration of LCA and emergy methods are discussed in [START_REF] Rugani | Improvements to Emergy Evaluations by Using Life Cycle Assessment[END_REF][START_REF] Raugei | Integrating Emergy into LCA: Potential Added Value and Lingering Obstacles[END_REF].

Almeida et al. [START_REF] Almeida | Emergy as a Tool for Ecodesign: Evaluating Materials Selection for Beverage Packages in Brazil[END_REF] applied the emergy accounting based on data from a previous Brazilian LCA study of the PET and aluminum packaging production chains for beverage, including the recycling stages. This analysis contributed for the selection of the materials and processes during the product design stage. In this case, the inventory data was based on the information reported by group of Brazilian companies, collected through questionnaires, including data on raw materials use and consumption, energy, semimanufactured and auxiliary materials and fuels for transport, considering only the Brazilian domestic production. The use of LCIs for calculating emergy was performed taking into account aspects about coherence of emergy algebra rules, the structure of the inventory data and the boundaries of the considered systems. In this work, similarly to Almeida et al. [START_REF] Almeida | Emergy as a Tool for Ecodesign: Evaluating Materials Selection for Beverage Packages in Brazil[END_REF], the production of PET resin as preform for beverage packages is also analyzed. However, a more comprehensive analysis is sought regarding the specific emergies of eleven intermediates products that make up this petrochemical chain, considering each of its processes separately based on a different inventory for each intermediate product. The data structure used in this study has a higher level of detail since the eleven intermediate products are tracked back, considering the cumulative amounts of all the elementary flows throughout the life cycle of each one. More details about data sources and methods will be described in the following sections.

The objective of this study is to apply an LCI-based emergy synthesis to determine the UEVs of the products for and within the polyethylene terephthalate production chain (PET), based on the information about the European petrochemical production. These UEVs are compared with those obtained by Bastianoni et al. [START_REF] Bastianoni | The Solar Transformity of Petroleum Fuels[END_REF] and Sha et al. [START_REF] Sha | Solar Energy Footprint of Ethylene Processes[END_REF], calculated in the traditional way. Fig. 1 shows the stages of the PET production chain. The first stage is the extraction and processing of crude oil and natural gas. These resources are a mixture of hydrocarbons which can be derived into chemical compounds that are used as raw material of other products along the production chain. The main fraction of crude oil used in the petrochemical industry is naphtha. The production route includes several unitary processes, each with an important contribution in the total balance of resources. At the end of the production chain, the thermoplastic resin in solid state (bottle-grade) is obtained, and used as raw material for the production of bottle packaging, via injection or blown.

Emergy method

Emergy is a measure in solar equivalent joules (seJ) of all contributions received by any system including the production ones. These contributions come in the form of material and energy flows, fuels, metals money, and labor. The result is a scientific measure of the energy previously used, directly or indirectly to obtain each flow. Emergy tracks all things to their source in the biosphere, the supplier, recognizing the environmental effort needed for the production of a good or service, in which lies the value of a resource, ensuring the use optimization [START_REF] Ulgiati | Shared Wealth or Nobody's Land? The Worth of Natural Capital and Ecosystem Services[END_REF].

The emergy results are presented in a common unit, called solar equivalent joules, seJ, and unit emergy values (UEV) are used for the conversion of one type of energy to another. The UEVs can be expressed as seJ /unit (e.g. grams, liters, currency) and the term transformity is used when the UEVs are expressed in seJ /J. As a measure of energy conversion and process efficiency, the UEVs refer to one unit of product that can be obtained from the lowest emergy investment.

The emergy tables are built based on the recorded information about the input and output flows of the system analyzed. The amount of each input is multiplied by its respective UEV, giving as a result the emergy of each input, which can be summed to determine the total emergy of the process and, thus, of the product. It should be noted that flows related to the plant construction phase, infrastructure and maintenance, were not taken into consideration in this work, since their influence in the total emergy required is around 4%, and considered negligible [START_REF] Bastianoni | The Solar Transformity of Petroleum Fuels[END_REF][START_REF] Sha | Solar Energy Footprint of Ethylene Processes[END_REF]. Similarly, since this study intends to evaluate only the technological efficiency of each process, labor and services inputs are not included. These flows depend, to a large extent, on the local social and economic structures, and consequently, limit the assessment to a given region and the overall scope of the analysis restricted. As the results refer to technological aspects, they can be used for comparison with other production systems of the same products, and assist strategic decision making.

LCI Databases

The databases comprise flows that are the result of tracking back each product along the production chain, including upstream processes as many as needed to identify the environmental source. Hence, the only economic or transformed output in the resulting data is the functional unit: 1 kg of product ("at gate" representing the average of European industrial production). All other values correspond to cumulative totals of all operations traced back to the extraction of raw materials from nature [14]. Such information is contained in documents known as Eco-profiles, which include all streams belonging to the processes from the extraction of natural resources to obtaining 1 kg of each product, ready for transport or transfer to the consumer. The Eco-profiles are established following the ISO 14040-44 standards and the International Reference Life Cycle Data System (ILCD) 1 . The databases used in this work are part of the Eco-profile Program and Environmental Product Declaration (EPD) of the Association of Plastics Manufacturers, PlasticsEurope.

Results and Discussion

Table 1 shows the UEVs calculated for PET and for 10 of its precursors. The calculation was performed using emergy tables to quantify the emergy contributions of input flows to the production system for 1 kg of each product. The different UEVs determined represent the emergy intensities per gram of product (seJ /g). Table 1 also shows the UEVs previously calculated by other authors [START_REF] Bastianoni | The Solar Transformity of Oil and Petroleum Natural Gas[END_REF][START_REF] Sha | Solar Energy Footprint of Ethylene Processes[END_REF][START_REF] Morales | Life Cycle Assessment of Gasoline Production and Use in Chile[END_REF]. Differences may be attributed to assumptions for the calculation and to the processes intrinsic characteristics. In the case of ethylene, Sha et al. [START_REF] Sha | Solar Energy Footprint of Ethylene Processes[END_REF] assumes a yield of 31% of ethylene based on naphtha and considers other coproducts of the steam cracking process. Differently, the UEVs of this work are result of tracking back the inflows that belong to production route of 1 kg of ethylene (the same for all other products). Therefore, instead of yield conversion of the raw material, it is taken into account the elementary feedstock content in the product, i.e. crude oil through naphtha, tracked back to the first stage of the production chain (crude oil extraction). In this regard, it is worth noting that naphtha and other petroleum derivatives are not considered as co-products, but as splits of crude oil with different densities [START_REF] Bastianoni | The Solar Transformity of Petroleum Fuels[END_REF]. Regarding to the specific emergy of PET, the differences observed correspond to dissimilar levels of efficiency in the use of resources for production. However, there is some uncertainty by evaluating and comparing production systems from different countries or regions, since the emergy results do not directly reflect dif-ferences between systems for reasons other than technological, e.g., political or socio-economic aspects. Therefore, lower UEVs are the outcome of the highest efficiencies in the use of resources in highly industrialized countries or regions with advanced production technology. In this way, the emergy results can contribute in selecting production technologies with lower environmental costs, ensuring a more appropriate technological configuration for the use of resources. In parallel, these results can be interpreted as measures of quality of energy by defining ratios between amounts of emergy required per joule of product, i.e., transformities (seJ /J). Thus, an estimate of the process efficiency, in terms of emergy, is obtained (Fig. 2). The transformity increases linearly along the production chain, as more inputs (energy and materials) are incorporated into the chain to obtain the next derivative. This result also establishes an expected range for UEVs of the petrochemical industry. From crude oil to the final product, the transformity approximately doubles its value, and all UEV's estimated lie within a range between 3.99x10 9 seJ /g, from ethylene glycol, and, 6.40x10 9 seJ /g, from ethylene, which is the derivative with the largest emergy required per gram of the products of the chain. The tendency line also establishes the rate in which petrochemical transformations occur in the PET production chain. The expected range reduces the level of uncertainty in the UEVs selection for emergy estimations in the petrochemical industry, offering a possible alternative for future research to facilitate scientific and operative work on data collection to calculate UEVs in this sector.

Conclusions

In current scientific publications, emergy synthesis has been sparsely applied to the downstream production processes of extraction and refining of fossil fuels. In this article, the PET production chain was analyzed, from the perspective of resources and energy usage comprising a variety of intermediate products. The UEVs for petrochemical products were calculated and compared with the already existing in the literature; some of them are novel information (pyrolysis gas, xylene, para-xylene, ethylene oxide, ethylene glycol and purified terephthalic acid). Thus, this work contributes to the consolidation of the emergy databases and proposes an expectance range for the petrochemical industry as an approach that can be useful by applying the emergy method.

According to this study, it is considered that the use of LCIs in accounting emergy is a feasible and practical way to obtain reliable results. Additionally, it offers important contributions for integration and/or complementarity of both LCA and emergy methods.

2 2. 1

 21 PET Production System

Fig. 1 .

 1 Fig. 1. Production route of polyethylene terephthalate (PET) bottle-grade (Source: adapted from [12])

Fig. 2 .

 2 Fig. 2. Transformity values for derivatives of the PET production chain

Table 1 .

 1 Calculated unit emergy values (UEV) by product of the PET production chain and literature values. All the emergy measures in this work are related to baseline 15.83x10 24 seJ/year[START_REF] Odum | Folio #2: Emergy of Global Processes. Handbook of Emergy Evaluation[END_REF]. Calorific values between mass and energy in[START_REF] Bastianoni | The Solar Transformity of Oil and Petroleum Natural Gas[END_REF]: 4.19x10 4 J/g for oil, and 5.13x10 4 J/g for natural gas.

		UEVs*/ UEVs**from
		x10 9 (seJ/g)* literature	Reference
			(seJ/g)*
	Crude Oil	4.47	3.90 x 10 9	[2]
	Natural gas	4.14	3.69 x 10 9	[2]
	Naphtha	4.75	5.02 x 10 9	[4]
	Py gas	5.77
	Xylene	5.24
	P-Xylene	6.15
	Ethylene	6.40	1.69 x 10 10	[4]
	Ethylene oxide	5.40
	Ethylene glycol	3.99
	PTA	5.00
	PET	5.94	6.32 x 10 10	[4]

* **

Details about the Eco-profiles methodology, interpretation and data collection can be found at:http://www.plasticseurope.org/plastics-sustainability-14017/life-cyclethinking-1746/eco-profiles-programme.aspx


Volker Stich

Daniel Pause
email: daniel.pause@fir.rwth-aachen.de

Matthias Blum

Nina Hinrichs

A Simulation Based Approach to Investigate the Procurement Process and its Effect on the Performance of Supply Chains

Keywords: Procurement, Supply chain, System dynamics, Inventory management, Design of experiments

Influenced by the high dynamic of the markets the optimization of supply chains gains more importance. However, analyzing different procurement strategies and the influence of various production parameters is difficult to achieve in industrial practice. Therefore, simulations of supply chains are used in order to improve the production process. The objective of this research is to evaluate different procurement strategies in a four-stage supply chain. Besides, this research aims to identify main influencing factors on the supply chain's performance. The performance of the supply chain is measured by means of back orders (backlog). A scenario analysis of different customer demands and a Design of Experiments analysis enhance the significance of the simulation results.

Introduction

Today, manufacturing companies are confronted with the influences of a dynamic environment and the continuously increasing planning complexity [START_REF] Brecher | Integrative Production Technology for High-Wage Countries[END_REF]. Reduced time to markets, rising product diversity as well as complex multi-tier and world-spanning supply chains are faced with growing inter-connectivity of production machinery, enterprise resource planning systems and manufacturing execution systems. Due to globalization, the number of market participants rises resulting in a growing competition amongst the individual companies [START_REF] Rushton | The Handbook of Logistics and Distribution Management: Understanding the Supply Chain[END_REF]. In particular, different wage levels in developed and developing countries induce enhanced price pressure on established companies in high-wage countries [START_REF] Abele | Handbuch Globale Produktion[END_REF]. In order to remain profitable as a business, the industrial enterprises in high-wage countries must identify cost carrier of the production process in order to reduce unnecessary costs. This is why companies focus on the production steps with a high share of added value and reduce the depth of production [START_REF] Wannenwetsch | Integrierte Materialwirtschaft, Logistik und Beschaffung[END_REF]. A strong trend towards reduced inventory is sensed so that components are delivered "just-in-time" (JIT) for the production. Accordingly, the process of procurement must be designed in a way which ensures a smooth production. As part of inter-company value chains the individual view of procurement is not adequate anymore. Rather, the analysis and optimization of the whole supply chain continues to gain importance [START_REF] Schuh | Produktionsplanung und -Steuerung. Grundlagen, Gestaltung und Konzepte[END_REF]. This appears to be difficult in industrial practice due to unknown interactions of various parameters in the supply chain (e.g. interactions of the reorder level of the manufacturer on the backlog of the supplier are unknown). Considering these problems, companies lack on an efficient design of their procurement processes. In order to overcome the described issue, this paper presents an approach how to tackle the problem of inefficient procurement processes. Therefore, we designed a simulation model of a four-stage supply chain (sub-supplier, supplier, manufacturer and customer) covering all steps of the procurement process. The aim of simulating a supply chain is to display known interdependencies and phenomena and thus be able to improve the decision making process. In particular, different procurement strategies are investigated and evaluated in this paper. In order to further investigate the interactions of the parameters in the supply chain, a Design of Experiments approach was used. Hereby, the interactions of the parameters are investigated and principles how to design an efficient supply chain are derived.

State of the Art

Due to the close link between procurement, inventory management and production a separate analysis of these sections is not sufficient. Thus, the emphasis is put on the optimization of all companies involved in the value-added process (supply chain). To investigate the cooperation and acting of a supply chain various research approaches already exist. In the following these approaches are outlined. Moizer et al. (2014) examine the advantages of a close cooperation between the manufacturer and its suppliers of a retail supply chain and the influence of efficiency and performance. A simulation was used on the basis of a trial group consisting of 12 retailers in the US. It was shown that collaboration can cut costs, risks and inventory for both the retailer and their suppliers [START_REF] Elkady | A Decision Support Framework to Assess Grocery Retail Supply Chain Collaboration: A System Dynamics Modelling Approach[END_REF]. Langroodi and Amiri (2016) investigate the choice of the most appropriate region for order placements in a five stage multi-product supply chain, consisting of a customer, an incorporate retailer, manufacturer, material distributor and supplier, in four different regions using a System Dynamics model. A scenario analysis with varying costs and demands was conducted. The model aims to minimize the costs of orders between two stages consisting of transport, price for the product and order placement and thus choose the best supplier [START_REF] Langroodi | A system Dynamics Modeling Approach for a Multilevel, Multi-product, Multi-region Supply Chain under Demand Uncertainty[END_REF]. [START_REF] Hishamuddin | A Simulation Model of a Three Echelon Supply Chain System with Multiple Suppliers Subject to Supply and Transportation Disruptions[END_REF] analyze disruptions of supply and transportation on the system's total recovery costs and other performance measures in a three stage supply chain with multiple suppliers. Thus, different scenarios of disruptions combined by kind and location of disruption were established to evaluate system costs and stock outs. It was shown that transportation disruptions have more damaging effects than supply disruptions due to the higher lost sales quantity. In addition, disruptions in the earlier stages have a higher negative impact to the supply chain compared to later disruptions [START_REF] Hishamuddin | A Simulation Model of a Three Echelon Supply Chain System with Multiple Suppliers Subject to Supply and Transportation Disruptions[END_REF]. Li et al.

(2016) examine the dynamic risks effects in a chemical supply chain transportation system. Therefore, a System Dynamics model was built and risk scenarios were established regarding the probability and consequence severity in order to compare order fulfillment rate, transportation and inventory level to measure the performance. The major sources of risks transpired among other as breakdown in core operations, inappropriate choice of service provider and lack of inventory management. The researchers used only a questionnaire as the input for various risk scenarios which could be a source of bias. Thus, it would be necessary to use a more extensive data source [START_REF] Li | A System Dynamics Simulation Model of Chemical Supply Chain Transportation Risk Management Systems[END_REF]. This paper enables the user to evaluate different procurement strategies and interpret the influence of various parameters. The emphasis is put on the interplant relation instead of the internal production itself.

Methodology

System Dynamics is a methodology for modeling, simulating, analyzing and designing dynamic and complex issues in socio-economic systems. Simulation models based on System Dynamics contain four different types of elements [START_REF] Coyle | System Dynamics Modelling: a Practical Approach[END_REF]:

1. Levels represent state variables of the system 2. Flow variables symbolize temporal change of the state variables 3. Auxiliary variables are used for decision rules describing casual relations 4. Constants are parameters to be set for the simulation Supply chains mainly consist of inventory (information or material) as time based variables and flows as activities (transport of material and information). Decisions steer running activities and thus the state of the system [START_REF] Aberle | Management der Logistikkette[END_REF]. A superior aspect to other simulation models is the possibility of feedback loops within the model. Thus, it is suitable for analyzing complex problems [START_REF] Wienholdt | Dynamische Konfiguration der Ersatzteillogistik im Maschinen-und Anlagenbau[END_REF]. A common way to analyze a system's behavior using System Dynamics is a scenario analysis. This was done by using the tool Vensim.

Description of the Simulation Model 4.1 Model Structure

The model consists of a sub supplier, a supplier, a manufacturer and a customer (Fig. 1). Between the respective supply chain partners a material flow and an information flow is taking place. The sub supplier serves as an infinite source of order items and the customer is able to create different demand situations. The supplier and the manufacturer are modelled according to a simplified business structure, which is described in the following paragraph. The business structure both of the supplier and the manufacturer are composed of an arrival warehouse for incoming goods, a quality check (QC) for the incoming goods, a Fig. 1: Model structure production and a shipping warehouse from which the products are delivered to the customer.

The parameters contained in the model are shown in Table 1. Conducting a scenario analysis target inventory, lead time, α service level and production rate were defined for both the supplier and the manufacturer. The customer demand is induced by an Excel based data generator. Thus, based on several parameters different demand situations can be applied to the simulation model. An expected demand and a standard variation need to be specified prior to the simulation as well as the initial situation with regard to a so-called trend, season or a constant demand.

Procurement Process

In the beginning of the simulation a certain stock is available in the shipping warehouse from which the demand is satisfied. As soon as the stock reaches the reorder level a new order is placed with the supplier. Between the time of ordering and the time of delivery the order quantity is put in the open purchase quantity. Before a new order is placed both the stock amount in the shipping warehouse and the amount in the open purchase quantity is checked if the stock moved below reorder level. The order quantity varies depending on the order policy investigated. This paper puts emphasis on a variable order point (s,S and s,Q order policy), because the order policies using a fix order point are mostly obsolete today [START_REF] Gruen | Grundzuege der Beschaffung, Produktion und Logistik[END_REF]. The reorder level s, at which a new order is placed, establishes a link between the inventory level and the stochastic character of the demand. While the order quantity varies using a s,S strategy due to the stock replenishment up to a set target inventory a s,Q strategy purchases a fix quantity every time [START_REF] Kelle | The Effect of (s,S) Ordering Policy on the Supply Chain[END_REF]. However, in this study the order quantity using a s,Q strategy can vary by the size of the backlog. In case the company is not able to meet the full demand in one period this amount is considered for the following order placed at the supplier. The reorder level is defined by the safety stock and the material which is used for the daily production. The daily production is determined by the moving average production of past periods in order to avoid a high volatility. The safety stock depends on the volatility of the demand. When the demand fluctuates substantially, a greater safety stock is necessary to ensure a smooth production. Depending on the delivery reliability towards the customer a greater safety stock has to be held. Another factor that influences the safety stock is the time it takes to restock the warehouse, defined as lead time.

Results of the Simulation

Different scenarios of demand situations have been investigated to identify the best order policy. The results were compared by evaluating the quantity of the backlog. This variable is linked to the service level which in turn has a direct influence on the customer's satisfaction and thus the supply chain's long-term success. In the following the scenario of a seasonal demand is exemplarily presented. Fig. 2 illustrates the comparison of the ordered parts and delivered parts over time. Whereas the delivered parts do not vary between s,Q and s,S order policy, it is obvious that the backlog using the s,Q order policy is lower than the backlog of the s,S order policy. The s,Q order policy reorders the amount of backlog as well as the usual quantity and is thus able to better react on unstable demand situations. Figure 2 also indicates that the backlog of the supplier occurs more often and in a higher quantity than the backlog of the manufacturer.

Based on the simulation results a Design of Experiments analysis was conducted to visualize and identify the factors that influence the backlog of delivered parts most. The main effects charts in Figure 3 illustrate the examined factors (also see Table 1) and indicates if it has a positive or negative impact on the backlog when changing from a predefined minimum to a maximum value.

A horizontal line implies that there is no effect on the backlog, the steeper the line the greater the influence on the backlog. It is obvious that the greatest influence on the backlog of the manufacturer and supplier are the lead time Fig. 2: Results of the scenario analysis on the basis of a seasonal demand structure Fig. 3: Main effects charts for supplier's and manufacturer's backlog (L,L0) and the target inventory (HB,HB0). The backlog of the supplier increases with a greater lead time and a decreasing target inventory. The target inventory of the manufacturer and the lead time of the supplier have a positive influence on the backlog. A higher manufacturer's target inventory comes along with greater order quantities which leads to a higher backlog because the supplier is not prepared for these orders. The supplier can react by storing more inventories due to the negative effect as seen in the left graph (HB). Another fact which is seen in Fig. 3 is that the manufacturer's backlog is not much influenced by the actions of the supplier (lead time and target inventory). The line of the production rate between 500 and 10.000 pieces per day (PL L and PL H) as well as the α-service level (SG and SG0) in both plots are almost horizontal indicating a low influence on the backlog. After identifying the lead time and the target inventory (HB) as the major influencing factors, an analysis of the interaction between these parameters was conducted (Fig. 4). An interaction plot shows the interdependencies between particular factors when changing specific factor settings. Because an interaction can magnify or diminish main effects, evaluating interactions is extremely important.

Fig. 4: Interaction between target inventory (HB) and lead time

The lines in Fig. 4 are indicating the strength of the interaction between the parameters. If the lines are parallel to each other, no interaction occurs. The more nonparallel the lines are, the greater the strength of interaction is. Evaluating the supplier's backlog it stands out that there is a great influence between the target inventories (HB) of the manufacturer and the supplier. Due to this fact it would be advisable that the supplier and the manufacturer make arrangements on their target inventories for the purpose of a decreasing backlog. Apart from that only slight interactions are seen in the plot of the supplier's backlog. On the contrary the manufacturer's backlog shows almost no interaction between the target inventories (HB) of the manufacturer and the supplier. Even greater is the interaction between the manufacturer's target inventory (HB) and its lead time. It would therefore be advisable to choose the proper target inventory based on the lead time to the customer.

Conclusions and Outlook

In this paper, a simulation of a four-stage supply chain was presented and different order policies were compared. After introducing the basics of procurement and inventory as well as System Dynamics, the model structure was explained and two order policies were chosen for a comparison. It was shown that the lead time and target inventory are main causes for the supply chain's performance measured on the basis of the backlog. Due to the dependency of the backlog of the supplier by actions of the manufacturer, a close cooperation between all companies involved is advisable. The vendor managed inventory where the supplier manages the inventory and orders of the manufacturer is a method trying to decrease the backlog. In further investigations this method could be considered and implemented in the simulation model. Additionally, further parameter could be added to the model, which might influence the supply chain's performance. e.g. costs for inventory and procurement in order to further specify decision rules. Moreover, instead of using the backlog as a main measuring unit for the supply chain performance further objectives such as costs or average inventory level could be considered.

Table 1 :

 1 Parameters in the simulation model for the supplier and the manufacturer

	Code	Declaration	Setting Range
	HB	Target Inventory Supplier	500 -2000 pieces
	HB 0 Target Inventory Manufacturer	500 -2000 pieces
	L	Lead time Supplier	2 -14 days
	L0	Lead time Manufacturer	2 -14 days
	SG	α-Service Level Supplier	90 -100 %
	SG 0 α-Service Level Manufacturer	90 -100 %
	PL L	Production Rate Supplier	500 -10.000 pieces / day
	PL H Production Rate Manufacturer 500 -10.000 pieces / day

Acknowledgements

The presented research is a result of the Cluster of Excellence (CoE) on "Integrative Production Technology for High-Wage Countries" funded by Deutsche Forschungsgemeinschaft (DFG). Within the CoE "Integrative Production Technology for High-Wage Countries" several institutes at RWTH Aachen University are conducting research on fundamentals of a sustainable production strategy. The authors would like to thank the German Research Foundation DFG for the kind support within the Cluster of Excellence Integrative Production Technology for High-Wage Countries.


Ricardo Pinto Ferreira

Andréa Martiniano
email: andreia.martiniano@gmail.com

Arthur Ferreira

Marcio Romero

Renato Jose Sassi

Container Crane Controller with the Use of a NeuroFuzzy Network

Keywords: Container crane, Artificial neural network, Fuzzy logic, Neuro fuzzy network

ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

The container crane is widely used to transfer heavy loads in ports and shipyards. This transfer is desirable that the container crane transport the loads to the desired position as quickly and as accurately as possible without colliding with any other equipment. This rapid movement naturally induces undesirable balance of the container, which could cause damage to the load and other types of hazards, also reducing the performance of the operation. Therefore, these oscillations in the track must be damped before another container come into operation. Thus, the performance transshipment loses the desired efficiency, increasing the cost involved in the operation and the risk of accidents with heavy loads that are transferred continuously throughout the operation. Fuzzy Logic (FL) was developed in 1965 with the work of [START_REF] Zadeh | Fuzzy Sets[END_REF] to represent the uncertain, imprecise and vague knowledge. FL translates the ambiguous information, imprecise, uncertain, in numeric values and includes the human experience in intelli-gent systems, processed by computer, and versatile for solving real problems [START_REF] Pacheco | Sistemas Inteligentes de Apoio à Decisão: Análise Econômica de Projetos de Desenvolvimento de Campos de Petróleo Sob Incerteza[END_REF]. The use of FL has been growing in several areas of knowledge, as in the control of electromechanical systems, character recognition, robotics, elevator systems, landing aircraft, etc. The growth in the use of FL is due to its great simplicity of implementation, and require little tired in its modeling, which provides both for the manufacturer, which reduces their costs, and the final consumer who acquires a more efficient product [START_REF] Costa | Aplicação de Técnicas de Modelagem e Controle em Sistemas Tipo Ponte Rolante[END_REF].

Artificial Neural Networks (ANNs) are a from the Artificial Intelligence technique based on simulation of the functioning of the brain by computer data structures, the great motivation of the use of this technique in performing tasks that require fault tolerance, flexibility, imprecision and parallelism [START_REF] Haykin | Redes Neurais -Princípios e Práticas[END_REF]. The NeuroFuzzy Network (NFN) ANNs are applied in various fields such as modeling, time series analysis, pattern recognition, signal processing, control, image recognition and data mining [START_REF] Haykin | Redes Neurais -Princípios e Práticas[END_REF][START_REF] Bigus | Data Mining with Neural Network: Solving Business Problems from Applications Development to Decision Support[END_REF][START_REF] Maass | Pulsed Neural Networks[END_REF][START_REF] Silva | Redes Neurais Artificiais para Engenharia e Ciências Aplicadas[END_REF][START_REF] Braga | Redes Neurais Artificiais: Teoria e Aplicações[END_REF][START_REF] Goldschmidt | Data Mining: Conceitos, Técnicas, Algoritmos, Orientações e Aplicações[END_REF][START_REF] Ferreira | Study On Daily Demand Forecasting Orders Using Artificial Neural Network[END_REF]. The NFN is the combination of FL and ANNs, some techniques may be combined to generate the so-called hybrid systems, or hybrid architectures. The advantage of this type of system must be obtained by cooperation combination of techniques [11. NFN is an alternative to the development of new studies seeking the possible applications in engineering problems. Several studies have been published to control the cranes containers, describing some recent work related to this study that bring interest [START_REF] Costa | Aplicação de Técnicas de Modelagem e Controle em Sistemas Tipo Ponte Rolante[END_REF], [START_REF] Mohammed | Fuzzy Logic Controller for Overhead Cranes[END_REF][START_REF] Chang | Adaptive Fuzzy Controller of the Overhead Crane with Nonlinear Disturbances[END_REF][START_REF] Yu | Stable Adaptive Compensation with Fuzzy CMAC for an Overhead Crane[END_REF][START_REF] Zhao | Fuzzy-Model-Based Control of an Overhead Crane with Input Delay and Actuator Saturation[END_REF][START_REF] Smoczek | Evolutionary Algorithm-Based Design of a Fuzzy TBF Predictive Model and TSK Fuzzy Anti-Sway Crane Control System[END_REF][START_REF] Qian | Fuzzy-Logic-Based Control of Payloads Subjected to Double-Pendulum Motion in Overhead Cranes[END_REF]. Cranes controller using fuzzy clustering techniques [START_REF] Sadati | Design of Again-Scheduling Anti-Sway Controller or Tower Cranes Using Fuzzy Clustering Techniques[END_REF], parallel neural network for crane control [START_REF] Lee | Parallel Neural Network Combined with Sliding Mode Control in Overhead Crane Control System[END_REF], adaptive control crane [START_REF] Nguyen | Nonlinear Adaptive Control of A 3D Overhead Crane[END_REF]. The aim of the paper was to present a container crane controller pre-project using a NFN.

2

Theoretical Bases

Container Crane

Figure 1 illustrates a crane container with its basic elements: the cart, (responsible for the displacement), the opening angle ( ), the load (container), cable (support), the track and the direction of the force gravity.

Fuzzy logic

FL is a mathematical theory, which aims to model human reasoning, mimicking the human ability to make decisions in uncertain and imprecise environments, expressed by a set of linguistic variables [START_REF] Pacheco | Sistemas Inteligentes de Apoio à Decisão: Análise Econômica de Projetos de Desenvolvimento de Campos de Petróleo Sob Incerteza[END_REF], [START_REF] Goldschmidt | Data Mining: Conceitos, Técnicas, Algoritmos, Orientações e Aplicações[END_REF]. It uses the concept of FL as the mathematical tools in fuzzy sets [START_REF] Passino | Fuzzy Control[END_REF]. In this case, we used the nomenclature of fuzzy sets defining them as a class of continuous variables objects. Those sets are characterized by membership functions, which indicate for each element a degree of relevance 0-1 [START_REF] Nicoletti | Fundamentos da Teoria de Conjuntos Fuzzy[END_REF]. For a wide range of physical phenomena it is difficult to clearly establish whether an element belongs or not a particular set. Thus, [START_REF] Zadeh | Fuzzy Sets[END_REF] proposed a broader characterization, such that membership function may assume continuous values between (zero) and 1 (one). The concepts of intersection, union, complement, convexity, etc., are extended to those sets and various properties of these notions in the context of fuzzy sets are established in the work of [START_REF] Zadeh | Fuzzy Sets[END_REF]. The membership functions have various forms, depending on the concept you want to express and can be set from the user's needs, but it is common to use standard membership functions, such as: triangular function, trapezoidal and Gaussian, or even, through analytics.

The central question for consistency to model a system by FL is the determination of a rule base representing the satisfaction of its dynamics, that is, as the input variables are related to each other, what there are outputs and, from that, their corresponding associated errors are determined. Therefore, the accuracy of the model is directly proportional to the adhesion between the real dynamics of the system and the basic proposal rules to represent it [START_REF] Zadeh | Fuzzy Sets[END_REF]. Related systems some features where the application of FL is necessary or beneficial. Such complex systems are difficult to model, as an example we can mention: systems controlled by human experts, systems with inputs and complex and continuous outputs, systems which use the human observation, as starters or as the basis for rules, systems that are naturally inaccurate as the description systems is extremely complex [START_REF] Mcneill | Fuzzy Logic: A Practical Approach[END_REF]. The application of FL for predicting or monitoring for a given system is characterized by use of an inference engine. This feature makes it necessary that the events displayed in the entry must necessarily be classified in one of these rules [START_REF] Simões | Controle E Modelagem Fuzzy[END_REF].The establishment of the inference engine that simulates a system involves two stages: the premises of all the rules are compared to the controlled inputs to determine which rules apply in a given situation, then the conclusions are established using the rules which have been determined. To represent the inference mechanisms in fuzzy sets, we used the concept of fuzzy relationship, which generalizes the concept of present relations in the Classic Set Theory and represent the degree of association between elements of two or more fuzzy sets [START_REF] Simões | Controle E Modelagem Fuzzy[END_REF].

Artificial Neural Networks

The ANNs are models inspired in brain structure aiming to simulate human behavior in processes such as learning, adaptation, association, fault tolerance, generalization and abstraction [START_REF] Haykin | Redes Neurais -Princípios e Práticas[END_REF], [START_REF] Silva | Redes Neurais Artificiais para Engenharia e Ciências Aplicadas[END_REF], [START_REF] Simões | Controle E Modelagem Fuzzy[END_REF].

In the ANNs learning occurs through a set of simple processing units called artificial neurons. In Figure 2 is shown a representation of the artificial neuron. the data is observed (data vectors) neuron input (X1, ..., Xn), the neurons of the input layer (W1J ..., Wnj) with their respective weights, then immediately the additive junction or sum represented by the letter sigma, then the activation function (and finally the output (y). In a conventional computer system, if a failure part, in general the system as a whole deteriorates, while in an ANN, the fault tolerance is a part of architecture, due to its distributed nature processing. If a neuron fails, your erroneous output is overwritten by the correct output of its neighboring elements. So, at an ANN exhibits a soft performance degradation instead of presenting a catastrophic failure [START_REF] Haykin | Redes Neurais -Princípios e Práticas[END_REF]. One of the first ANNs, whose architecture is based on the biological neuron, has been proposed by [START_REF] Mendel | Reinforcement-learning Control and Pattern Recognition Systems. Adaptive, Learning and Pattern Recognition Systems[END_REF] the Perceptron. The purpose of this network is to classify the inputs xi (or stimulus) into two classes by a hyperplane. For the simple case of a space in two dimensions, the hyperplane is reduced to a straight line whose equation is represented in Equation 1.

∑ 𝑥 𝑖 𝑤 𝑖 + 𝑤 0 (1)
The activation is performed through artificial neuron activation function, which performs similar to the biological neuron synapse task, transmitting or blocking nerve impulses. In general, learning Perceptron networks is through the adjustment of synaptic weights. The value of the synaptic weight W (t+1) at the instant t+1, its will be determined on the basis of its value in the previous iteration wt, as in Equation 2.

𝑤 𝑖 𝑡+1 = 𝑤 𝑖 𝑡 + ∆𝑤 𝑖 𝑡 (2)
The updating of the weights depends on the algorithm, but generally is based on minimizing the error αi, between the values proposed by the network and outputs yi desired, as Equation 3.

𝜀 𝑖 = ∑ 𝑤 𝑖 𝑥 𝑖 -𝑦 𝑖 (3)
Thus, the learning (or training) on an ANN is defined as the iterative adjustment of synaptic weights to minimize errors [START_REF] Haykin | Redes Neurais -Princípios e Práticas[END_REF]. A general definition of what constitutes learning in an ANN can be expressed as a learning process by which the parameters are adjusted through a continued form in which the network is operating by particular way to the setting of the parameters occur. Several methods for learning have been developed and can be grouped into two main paradigms: supervised learning and unsupervised learning. In supervised learning, there is a prior knowledge of the values of xi yi inputs and their outputs. In this set of ordered pairs (xi, yi), that is known a priori gives the learning database name. The most widely used algorithm is the retro error propagation (error back-propagation) used by the MLP type ANN used in this work.

A Multilayer Perceptrons is one of the most used ANN in classification. The ANN architecture MLP typically consist of a specification of the number of layers, type of activation function of each unit and weights of connections between the different units should be established for the construction of the neural architecture [START_REF] Haykin | Redes Neurais -Princípios e Práticas[END_REF].

The error back-propagation training algorithm works as follows: shows a pattern in input layer of the network, this pattern is processed, layer by layer, until the output provides the processed response, fMLP, calculated as shown below in Equation 4. where vl and wlj are synaptic weights; bl0 and b0 are biases; and φ the activation function.

                  Non l l lj l MLP b b x w x f 1 0 0 ) (    (4)
Learning an ANN, in most cases, it happens to a subset of examples (data vectors) which define the so-called training set and ANN testing is performed with another subset of examples (data vectors) which define the so-called test set.

The ANNs can be trained using random initial values for the weights of connections. The learning parameters are initialized and data vectors training patterns are presented to the ANN. Throughout the training progress the connections weights are adjusted and you can monitor the performance of ANN [START_REF] Haykin | Redes Neurais -Princípios e Práticas[END_REF].

Neuro Fuzzy Network

Some techniques can be combined to generate the so-called hybrid or hybrid architectures systems [START_REF] Goldschmidt | Data Mining: Conceitos, Técnicas, Algoritmos, Orientações e Aplicações[END_REF]. The advantage of this type of system is due to the synergy obtained by combining two or more techniques. This synergism reflects in getting a more powerful system (in terms of interpretation, learning, estimation parameters, training, among others) and with fewer disabilities [START_REF] Pacheco | Sistemas Inteligentes de Apoio à Decisão: Análise Econômica de Projetos de Desenvolvimento de Campos de Petróleo Sob Incerteza[END_REF], [START_REF] Sassi | An Hybrid Architecture for Clusters Analysis: Rough Setstheory and Self-Organizing Map Artificial Neural Network[END_REF]. The purpose of this combination is to get good ability to learn and adapt to the needs to solve real-world problems, ideal for applications such as identification, prediction, classification and control [START_REF] Pacheco | Sistemas Inteligentes de Apoio à Decisão: Análise Econômica de Projetos de Desenvolvimento de Campos de Petróleo Sob Incerteza[END_REF], [START_REF] Simões | Controle E Modelagem Fuzzy[END_REF]. NFN is the term used [START_REF] Mendel | Reinforcement-learning Control and Pattern Recognition Systems. Adaptive, Learning and Pattern Recognition Systems[END_REF] for approaches that have the following properties: (i) Items are based on FL and are trained by a learning algorithm derived from one of ANNs. The learning procedure (heuristic) operates in local information, and causes only local changes in the foundation of NFN; (ii) Have three layers where the first layer is the input variables, the middle layer (hidden) represents the inference rules and the third layer is the output variables; (iii) Can always be interpreted as an inference engine.

Since not all learning templates specify procedures for creation of fuzzy rules; (iv) The learning procedure of NFN transforms the semantic properties of a fuzzy system into a set of descriptions. This results in restrictions that may become relevant changes to system parameters, however, not all approaches in a NFN possess this property; (v) Near an n-dimensional function that is defined in part by training data.

Materials and Methods

An ANN Multilayer Perceptron (MLP) combined with FL forming a NFN was adopted. The MATLAB software was used to generate the 15 fuzzy rules, the inference model and the response surface. The hardware platform used in the experiments was a computer with Intel® Core ™ 2 Duo CPU T6600 2.20 GHz with 4.00 GB of memory, 1 TB hard drive. To model the fuzzy membership functions of the speed of moving container bridge we used three Gaussian functions: low, medium and high. To model the fuzzy membership functions with the angle of the crane container were used five Gaussian functions: large negative angle, small negative angle, angle zero, small positive angle and large positive angle. The tractive power was modeled in three functions of Gaussian relevance: low, medium and high [START_REF] Zadeh | Fuzzy Sets[END_REF]. The parameters used in ANN were: number of input neurons equal to 2 (the fuzzy inference to: speed and angle), the number of layers equal to 2, the number of neurons in the hidden layer equal to 10, the initial rate of learning equal to 0, 3 with decay 1% every 20 times, starting time factor of 0.3 to decay 1% every 25 times, stopping criterion was the maximum number of times equal to 150. the ANN training was sequential (online), and the processing time was 5 s. The output of the NFN was the tractive power. Figure 3 shows the hybrid topology of NFN used in the experiment.

4

Results of Computational Experiments The results presented in the validation phase of NFN was satisfactory for the proposed model.

Conclusions

With the initial result is noted that the response surface 15 obtained through the fuzzy rules, allows pre-design a control mechanism, including the inputs and outputs required development system container crane controller. The NFN presented adherent experimental results the use of fuzzy logic associated with the ANN produced an engine capable of representing the dynamics of a crane container. The results recommend the implementation of the proposed NFN control. It contributes to the formulation of simple programming controllers.

Fig. 1 .

 1 Fig. 1. Container crane (Source: Adapted from [17, 21, 22])

Fig. 2 .

 2 Fig. 2. Representation of the artificial neuron (Source: Adapted from [4])

Fig. 3 .

 3 Fig. 3. Hybrid topology NeuroFuzzy used in the experiment.

Figure 4 (

 4 Figure 4 (a) shows the fuzzy membership functions generated by the 15 rules (Speed, Angle and power), and Figure 4 (b) gives the response surface. Figure 5 shows the validation phase of NFN.

Fig. 4 .Fig. 5 .

 45 Fig. 4. (a) Fuzzy pertinence functions. (b) Response surface area modeled by the 15 fuzzy rules