Hans Wortmann¹
email: j.c.wortmann@rug.nl

Wico Mulder

Reflections on Identity Management in Smart Industry: The Paradox of Theseus' Ship and Beyond

Keywords: Smart factories, Sustainability, Object life cycle, Digital shadows

Sustainable digitization of factories (and especially IoT) requires all data related to "things" (products, equipment, but also informational objects) to be stored for later reference in a so-called digital shadow. This paper addresses an identity question: "which data should be stored as a so-called digital shadow of an object?" and identifies two opposing principles, Single Source of the Truth vs Local Autonomy. The first principle keeps data objects small and uses links to other data objects. It expands object's life time. The second principle advices to keep objects large, reduces linkages but limits object's life time. The paper analyses these two principles for physical objects as well as for related informational objects. Some guidelines for application are given.

Introduction

The impact of data in the field of smart industry goes well beyond the level of optimizing production. Data is guiding the manufacturing processes. Whilst being designed, manufactured or shipped, the status of every product is kept in systems in the form of data. The same holds for related information that accompanies the product, such as the contracts, version information, ownership, user manuals or maintenance schedules. All of those are reflected by data. Once built, products leave the factory either serving as component of a different product, or starting to operate somewhere in our connected world. In a sustainable, circular economy, data that was collected during manufacturing of a product, will not only be used during the phase of manufacturing and operation, but also during refurbishment and reuse. Moreover, new data will be added. One can say that a modern data management platform1 maintains information of objects during the their full life cyclefrom cradle to grave. However, such view is not straightforward. When using concepts such as cradle or grave in relation to the physical world of manufacturing, our language is metaphoric. Physical objects are not born in a cradle and do not end in a grave: these are anthropomorphic notions. For example, if a component C disappears because it becomes part of an assembly A, should the life cycle of C be considered as ended ("grave")? In many cases, this question would be denied, because the usage of C may be monitored as part of the assembly A. Accordingly, does the life cycle of C end when the assembly A is discarded and scrapped? Not necessarily, the component C may be refurbished and reused elsewhere. So when does the life cycle of C end? Who responsible for the data? What is implicit in our usage of the term 'platform'? Maybe the lifecycle of C ends when C has no longer a necessity or purpose, although even this statement may be disputed. Also, the notion of a connected world is problematic. Loosely speaking, it means that objects (representing e.g. things and humans) are ubiquitously connected to the internet. However, the implicit meaning is that objects have references to other objects' data and that these can always be retrieved when needed. For example, manufacturing orders refer to products, to operations, to machines, and many other objects. Still, the assumption that such references can always be retrieved, is problematic. Objects are owned by applications and these applications have a finite life cycle. More fundamentally, relations between objects are temporary and references should therefore be time stamped. If component C is manufactured by supplier S according to manufacturing instructions I, how can we be sure that the right version of these instructions I are retrieved? In many cases, we cannot be sure, unless these instructions are stored together in a data management platform in the form of a so-called digital shadow (which we will explain in the next section). Accordingly, related to concepts such as smart manufacturing and the associated developments such as the internet of things (IoT) and cyberphysical systems (CPS), there are two questions which seem fundamental to be elaborated: (i) What is the life cycle of an object? Or more precisely: what are the criteria to create a digital shadow of an object or delete it? (ii) What is the boundary of an object? Or more precisely: what are the criteria to include related objects and their data in the digital shadow of an object?

Terminology Background

Before discussing the above questions, it is worthwhile to present some working definitions. In the field of software development people use the word object to model elements from the real world into their design. We would like to use more conceptual but more precise notions, namely digital shadows and avatars. The Definition of A digital shadow is a digital representation of an object that manifests itself in the world around us.

A digital shadow refers to an entity inside a digital environment, e.g. in a database, that contains all the data of one particular object which exists in our real world. A digital shadow is tightly coupled to that physical object. In the context of internet of things, the digital shadow holds an ip-address, which allows for interaction with other objects during the phase of creation as well as during its operation.

As an example, one can think of any object, e.g. a bus, a plane or a cow, or one of their constituting components. Whenever we want to store or retrieve information from such an object, we do this via its digital shadow. Anyone who wants to have information about a particular thing or product X can do so via its digital shadow X'. This also holds for any object Y which needs to exchange (retrieve or store) data with object X. As depicted in figure one, there is one important constraint to take in mind; namely that Y cannot interact with X' directly, but only via its own digital shadow Y'. Fig. 1. Schematic picture of objects that exist in our physical world (denoted with X and Y) Together with their digital shadows (denoted with X' and Y'). The dashed lines show that X and Y are connected with their digital shadows. X and can Y communicate with each other via their digital shadows, as denoted with the solid line between X´ and Y´.

Thus, there is an important design principle for digital shadows: it is not allowed to have a direct connection between an object Y and a digital shadow X´. As an example think of a bus B having a digital shadow B' and an organization O (owning the bus) that wants to have access to the maintenance schedule of this particular bus. Suppose also that a traveler T (taking that bus) is interested in information about the actual time schedule of that particular bus.

As we see in many contemporary IT architectures, B' will be accessed by both O and T. Such IT architectures require multiple interfaces and something like a role-based access system. But as the number of interactions increase (which will happen given the evolution of internet of things) maintenance and flexibility reasons imply to automate the management of those interfaces.

A possible way to do this is to make use of the concept of digital shadows and let the interaction with B' take place via two other digital shadows O' and T'. This allows for more flexibility from an IT maintenance perspective, and possibilities for time-dependent, automated managed interfaces.

An example in the area of smart factories could be the manufacturing of constituents of an airplane which are manufactured by multiple organizations. During the phase of creation a digital shadow of those constituents serves as a digital product dossier. Many vendors, customers, shipping companies can have access to this dossier. Also machines can access the products bill of materials via this digital dossier. Later on, when the plane is in operation, information about maintenance schedules may be used by various groups of users. E.g. flight carrier organizations or insurance companies, passengers that following that particular plane.

Fig. 2. Schematic picture stressing the design principle of digital shadows

It's a small step here to think of complete mimicked worlds of goods, plants and organizations that manifest themselves as a complete universe within a cloud environment. So far, we talk about a digital shadow as a passive set of data inside a platform that can provide access by means of a (web) interface. Now, if we extend this concept to an active entity, that is something that can be programmed to perform tasks we could use notion of avatar2. Avatars are quite similar to the concept of agents [START_REF] Jennings | Agent-based Control Systems: Why Are They Suited to Engineering Complex Systems[END_REF][START_REF] Wooldridge | MultiAgent Systems[END_REF], but with one important restriction: they are uniquely connected to a (unique) object in our real world. The definition of an avatar is an active digital representation of an object that manifests itself in our physical world.

Avatars can be useful in situations where information about status and quality needs to be exchanged frequently or under certain restricted conditions. They play a role in local decision making and in the exchange of information with various stakeholders inside and across organizational boundaries, e.g. in production chains or when interacting in an Internet of Things context. Avatars can also be useful for simulation purposes and the analysis of what-if scenarios in situations where information is only locally available. A data management platform, as we mentioned in the previous section, can be regarded as a habitat for avatars.

3

Theseus' Ship and Beyond

Physical Objects

With these two concepts in mind, it is possible to elaborate on the questions mentioned in the introduction of this paper. The first question, related to the life cycle and identity of (physical) objects raised interest from philosophers in ancient times. In the form of Theseus Ship paradox, it was introduced by Plutarch in the 1st century, and it remained in philosophers interest until modern times. However, a related question was earlier posed by Heraclitus (6th century BC), who discussed the possibility to enter twice in the same river. Theseus Ship paradox goes as follows: "The ship wherein Theseus and the youth of Athens returned from Crete had thirty oars, and was preserved by the Athenians down even to the time of Demetrius Phalereus. They took away the old planks as they decayed, putting in new and stronger timber in their places, in so much that this ship became a standing example among the philosophers, for the logical question of things that grow; one side holding that the ship remained the same, and the other contending that it was not the same [START_REF] Plutarch | Theseus[END_REF]. Plutarch thus questions whether the ship would remain the same if it were entirely replaced, piece by piece" [2].

In modern times, the same issue emerges for our industrial society. Basically the same question emerges for many industrial products, viz. when to introduce a new identification for changing products. For reasons of conciseness, we describe here the solution adopted for standard assembled products, known as the form, fit, function rule. In many industries the so called Form-Fit-Function rule is applied to the problem at hand [START_REF] Romero Rojo | Obsolescence Management for Long-life Contracts[END_REF]. This rule states that companies will define a new item replacing an old one, if: (i) The item has a new form and/or; (ii) The item has a new fit (e.g. new tolerances) and/or, (iii) The item has a new function.

Therefore, new raw material to be used for an item, for example, is in itself not a reason for defining a new item. Also, if the item would get a new price, if it were stored in another warehouse, or if documentation of the item would be changed, this is not a reason for defining a new item or for issuing a new item code number.

But how can companies then keep track of significant changes that do not change the form, fit or function? For example, how can companies reflect the fact that the weight or the carbon footprint of a product has become much less due to the use of other materials? For these purposes, the notion of versions exist in manufacturing industries. The FFF-rule goes together with a versioning policy. This policy states, that items can have versions, and that a new version will be issued for all changes in the item documentation, which don't violate the FFF-conditions.

If something changes in the definition of an item O inside a product P, but there is no new form, fit, or function regarding P, then there is no reason to define an entirely new item of product P. In this case, a new version of O will be created.

Informational Objects

The notion of versions is crucial in the FFF-rule. However, what is a version? First of all, it should be acknowledged that the FFF-rule does not refer really to physical products, as we are tempted to believe, but to so-called informational objects. informational objects are objects that describe physical objects. Versions are no exception. Versions do not refer to physical instances, but to the informational description of these instances.

The question, what a version really is, can now be answered. A version is a new (or updated) description of a standard physical product. What makes a version different from other informational objects? Obviously, the fact that a (new) version refers to a previous version, and carries forward some attribute values or other informational elements (e.g. methods) from the previous version. Because the FFF-rule stems from the pre-digital era, it is not exactly defined which informational elements are carried forward.

Single-version-of-the-truth vs Self-containedness

In practical discussions about smart manufacturing, there are two principles which can be encountered. These principles are also underlying much academic work, although these principles are (to our best knowledge) not elaborated in the context of smart manufacturing. These principles are: (i) The principle of single version of the truth which states that data should always be retrieved from their source. Data kept by the digital shadow is often a reference to other digital shadows; (ii) The principle of autonomy or self-containedness. This principle states that all data describing an object should reside in its digital shadow or under control of its avatar.

The principle of single-version-of-the-truth tries to avoid redundancy, because redundant data are difficult to maintain: there are always updates which get lost. Therefore, this principle states that copying data or documents should be avoided. Data in e.g. digital shadows of objects should refer to data in other objects whenever such sources exist. When applied to versions of physical products, the principle states that a new version should contain only information in which the new version differs from the old version and all other information should be retrieved from the older version. When applied to components that are part of assemblies, the principle states that digital shadows of assemblies should not contain the information about the components, but rather refer to the digital shadows of these components.

For versions of software products the principle of single-version-of-the-truth leads to software architectures based on Software-as-a-Service (SaaS) principles. Therefore, the principle assumes that ownership of data is well organized and remains available over a long period of time. Accordingly, informational objects should have a long life cycle in this view, and hardly ever be deleted, because there may always remain links which require information form these objects. Also, the platform on which avatars or digital shadows reside, are assumed to have a long life cycle.

The principle of autonomy aims at robustness. Physical objects should have digital counterparts which are self-contained and proactive. Physical objects as components, parcels, tools, or machines should be enabled to take initiative, communicate, negotiate and get decisions taken. Advocates of the principle of autonomy are not primarily interested in avoiding redundancy. They do not argue against copying of data. They acknowledge the fact that objects may need updates from other objects, but they claim that e.g. publish-and-subscribe protocols are sufficient means for this purpose. They also do not have SaaS architectures in mind. Rather, they see smart manufacturing as consisting of decision-making applications where avatars interact with each other. In addition, they see analytical applications, where digital shadows of objects of the same type are analyzed by human professionals or by artificial intelligence applications. These applications typically take a broad view on the objects analyzed, and therefore many data are taken into the digital shadow.

Because the necessary data are carried in the digital shadow of the object, there is less interest in the longer life time of objects. Digital shadows and other digital objects are seen as created for a certain purpose, and when the purpose vanishes, the digital object or the digital shadow may vanish as well.

Discussion

Digital Assemblies

It is interesting to note that advocates of both principles see information objects largely as being constructed from other information objects. The term digital assembly can be coined for this process. This leads to the question, if the Theseus ship paradox is also applicable for digital assemblies. The answer is yes, there is an issue with the identity of digital assemblies, but there is also an important difference: if a digital component is taken into a digital assembly, the original component does not disappear. It can either be copied into the new object, according to the principle of autonomy or it can be referenced in the new object, according to the principle of single-version-of-the-truth.

It is also interesting that advocates of both principles refer to earlier experience with integration problems. Advocates of the first principle are well aware of the difficulties of heterogeneous systems and the advantages of open standards, web services and common databases. They claim that redundancy should be avoided. Advocates of the second principle are also well aware of integration problems. They claim that integration should be avoided.

Ownership

It is obvious that the advocates of the first principle (single-source-of-the-truth) must assume that the smart manufacturing organization has implemented proper ownership of digital shadows and of other digital documents. If data are not properly maintained, or if there is no ownership of data management platforms, the smart factory will not survive. This is not only required for the own organization, but also for partner organizations in New Product Development, in Supply Chain, in Distribution, in the product use phase and in recycling or refurbishment. However, also the advocates of the second principle (autonomy) must assume that their digital shadows are informed if related objects change. For example, if an assembly is dismantled, the components must re-appear. If new components failure modes are detected, the assembly digital shadow must become aware. As said, this will be implemented in autonomous systems by e.g. publish-and-subscribe protocols. However, these protocols also assume that ownership for platforms, applications and data is well established in the smart manufacturing organizations and with related stakeholders.

To be more precise, if a new digital object is made with its own life cycle, there should always be an owner. This owner either relies on references to existing data (e.g. for versions, following the first principle) or relies on copies (following the second principle), but ownership which guarantees the quality of the data cannot be avoided in smart manufacturing. In the end, the owner determines the solution chosen for the Theseus ship paradox in the case of digital documents.

Ownership means, that a party in the real world takes responsibility for the correctness of data ( [START_REF] Loshin | Who Owns Information? In Enterprise Knowledge Management: The Data Quality Approach[END_REF], [START_REF] Wende | A Model for Data Governance -Organising Accountabilities for Data Quality Management[END_REF]). The difference between the two principles resides in the nature of this responsibility. With single-source-of-the-truth, updates and changes are carried forward. With local autonomy, the data are frozen at the moment of creation. It is interesting that here the notion of shared ownership of frozen data becomes possible due to blockchain technology, a distributed public ledger of all transactions or digital events that have been executed and shared among participating parties [START_REF] Zuidam | Whitepaper Government as a Service[END_REF].

Can Digital Objects Have Digital Shadows and Avatars?

Initially, our discussion has been primarily focusing on the situation where there is a digital shadow and/or avatar which represents a physical product. However, the example of the FFF rule showed, that there are important informational objects in the digital world which may claim a similar status as physical objects. For example, an invoice may take initiative to be paid, a contract may urge to be signed. There is no reason to restrict the notion of avatar to representatives of physical objects. However, the digital shadow of a digital object may technically be realized in the same environment as the digital object itself. Conceptually, however, these is no reason to make a distinction between physical and informational objects in this respect.

Conclusion

In this paper, we posed two questions, related to sustainable smart manufacturing. As for the first question, we concluded that ownership of data objects is crucial in (smart) manufacturing. The life cycle of physical objects is ultimately related to a company's strategy in circular economy (including partnerships) but this can only be realized with properly assigned responsibility for data.

As for the life cycle of informational objects, our analysis revealed that informational objects are usually assemblies of other informational elements. The paper discussed two principles: (i) The principle of single-source-of-the-truth, which tends to keep longer life cycles and to keep distinct objects, leading to SaaS architectures; (ii) The principle of autonomous objects, which tends to have shorter object life cycles and allows overlapping objects, leading to Data Warehousing architectures.

These principles also provide conflicting guidelines for the second question. The first principle would create objects as small as possible with references to other objects, whereas the second principle would do the opposite. In practice, one sees combinations of these principles, still a guideline is to apply the first principle for objects which are used in applications that require real-time relational flexibility, whereas the second principle can be used for objects in applications that require robustness or historical compliancy.

Data management platforms are computer infrastructures that provide the means for the storage, connectivity and analysis of data

The concept of avatars is known in the field of computer gaming, but the name of the concept originates from ancient Hinduïsm beliefs in reincarnated bodies.


Nivaldo Luiz Palmeri
email: nivaldoluiz@uol.com.br

Oduvaldo Vendrametto

João Gilberto Mendes Dos Reis

Rosangela Kronig

Contributions of the Program Inovar-Auto to the Automotive Manufacturers in Brazil

Keywords: Competitiveness, Automotive industry in Brazil, Developing countries, Globalization

The Brazilian government intents to stimulate and modernize the national automotive industry. The Inovar-Auto program propose to improve the international competitiveness of automobile auto parts industry and to reduce the importations. This paper aims to verify the influence of the Inovar-Auto program in competitiveness of Brazilian automotive industry. To this end, we carried out a search regarding the investments to the following years of the program, the participation of international enterprises as stakeholders of the national industry and its next goals. The results showed that the major investments came from international companies.

Introduction

Since the 90s the Brazilian automotive sector has being part of an international transformation. The opened market for a free trade and economy growth made the Brazilian market more attractive to the transnational automotive companies. Thus, the manufactures initiated a remodeling process, including the relationship with the local suppliers, incorporating hierarchical strategies, global sourcing, follow sourcing and its variations [START_REF] Costa | Autopeças no Brasil: Mudanças e Competitividade na Década de Noventa[END_REF][START_REF] Furtado | La Transformation des Conditions d'insertion des Économies á Industrialisation Tardive dans L'économie Mondiale: Un Examen des Facteurs Généraux Suivi de leur Particularisation dans Cinq Secteurs Industriels[END_REF]. However, in the last five years, a trade balance deficit and a decrease of the automotive parts produced in Brazil jeopardize the future of the national supply chain [START_REF]ANFAVEA[END_REF].

The Brazilian government, as an attempt to change this scenario, issued the Acts 12.715 and 7.819 that created the Program to Incentive Technological Innovation and Aggregate the National Automotive Supply Chain (Inovar-Auto) [4,5]. The program aims to support the technological development, innovation, environmental protection, energetic efficiency and quality of both vehicles and auto parts. The Inovar-Auto has been build by a working group with participation of the Brazilian government, automotive enterprises, universities, associations, working unions and consultants [START_REF] Garcia | Inovar-Auto na Prática[END_REF]. The working group aim to evaluate if the program is robust enough to promote the national technological development to include Brazil in the international scenario.

The present study aims to evaluate the contributions of the Inovar-Auto program to the national automotive competitiveness. Thus, we analyzed the current legislation regarding the program, the investments proposed by the automotive sector in Brazil, and the nationality of the companies working in Brazil as well as the targets and requirements proposed by the national government. However, the initial proposal for the program has changed, since the financial resources, i.e. the incentive of the Inovar-Auto Program, has been applied not to either technological development or its transference, but to support new manufacturer plants, capacitation and marketing.

Methodology

We conducted an exploratory study based on a literature review. The information about to the Inovar-Auto program was obtained from the current legislation regarding it. In addition data were also collected from: specific publications of ANFAVEA (National Association of Manufactures of Automotive Vehicles); MDIC (Ministry of Development, Industry and International Trade); MCTI (Ministry of Science, Technology and Innovation); journals and specialized websites regarding the automotive sector as Automotive Business, Exame and others.

In order to evidence the divergences from the initial proposal of the program we analyzed the current legislation that supports it. Seventeen different legal acts have amended the program since the initial issued Act 12.715 in 20.112, until the Decree 8.544 in 2015.

These amendments represent requirements and procedures to capacitation of suppliers, expenses of strategic inputs, traceability, habilitations of companies and other factors that evidence the constant evolution the Inovar-Auto. We obtained the proposed investments of the manufacturers by the statistical report that was published in the website Automotive Business -Special Reports: Investments of Manufacturers 2011-2020, updated in August 2014 where the exchange rate is US$ 1 = R$ 2,40 e Euro 1 = R$ 3,30 [START_REF][END_REF].

The information about the majority control of the enterprises was collected either in the Exame magazine [8] or in the Internet. The main goals and the achieved targets are available in the MDIC website [9].

The present research provides information to analyze the proposed budged by the manufacturers in Brazil, the goals of the program and the expected results initially proposed. This dataset constitutes the base to the conclusion of the present study.

Literature Review

Brazil has one of the biggest markets for production and commercialization of vehicles. The national supply chain is vast and it includes basic inputs produc-tion, auto parts suppliers, the productive process and the distribution chain [START_REF]ANFAVEA[END_REF]. The country needs to improve the production, search and expand the commerce to new markets as well as to support the national market, and stimulate the competition, efficiency and increase the productivity in the automotive chain from the production to the commercialization [9].

The program Inovar-Auto stimulates the competitiveness, the search for efficiency systemic gains due to the productivity increase in the automotive supply chain, the stages of production as well as the technological and commerce network. It also encourages investments due to taxes reduction, consequently it increases the technological standards of the vehicles, parts, components, and vehicular safety. To the enterprises that fulfill the requirements in order to be licensed to the program may be applied an IPI reduction up to 30%. Fifty-five enterprises have the license regarding the program, comprehending 23 manufacturers, 15 importers and 17 project investors [9], and it must be renewed annually. In 2015, 25 enterprises applied to renew their licenses and were approved by the MDCI [9].

It is possible to correlate the stage of development level of the automotive sector and the economic development of a country. Countries with a developed automotive industry such as USA, Germany, Japan, South Korea, have competitive factors in common such as: majority part of the manufacturers and their main suppliers, knowledge and comprehension of developed technology, innovation, connections in the international market and success regarding the technological development [START_REF] Ruff | The Advanced Role of Corporate Foresight in Innovation and Strategic Management[END_REF]. On the other hand, in most of the developing countries as Mexico and Brazil, the industrial park depends on both foreign capital and technology. Some characteristics are familiar between these countries as geographical latitude, cultural aspects and dependence of international technology for the automotive segment. The foreign manufacturers working on developing countries are connected to their supplier, mostly working also on the country, for market reasons in order to maximize their profits [START_REF] Furtado | La Transformation des Conditions d'insertion des Économies á Industrialisation Tardive dans L'économie Mondiale: Un Examen des Facteurs Généraux Suivi de leur Particularisation dans Cinq Secteurs Industriels[END_REF]. The local suppliers represent the 2nd or 3rd level in the supply chain. Their products are limited to supply the local market and they are represented by small and medium companies that are focused on operation activities [START_REF] Costa | Autopeças no Brasil: Mudanças e Competitividade na Década de Noventa[END_REF]. These national small companies do not have conditions to fulfill the formal requirements to attend the Inovar-Auto Program. They are still part of the peripheral supply chain, producing exclusively technological obsolete components that are still being in use in national vehicles.

Evolution of the Program Inovar-Auto

The program Inovar-Auto represents an alternative to develop technology in vehicles produced in Brazil. Its main focuses are: safety; fuel consumption reduction; technological development; supply chain capacitation. However, it is still necessary additional efforts [START_REF]SIMEIA[END_REF]. Laws, decrees and acts represent the legislation Table 1 [START_REF] Garcia | Inovar-Auto na Prática[END_REF]12].

The program is currently: renewing the licenses; studying the availability of applying the surplus credit to next term of the licenses; conducting follow up auditing in the licensed enterprises to the continuation of the program during its term end in 2017 [START_REF] Garcia | Inovar-Auto na Prática[END_REF].

Planned Investments

The vehicles manufacturers have announced investments of US$ 22.3 billions in Brazil for the next years, where US$ 2.3 billions comprehends new manufacturers not yet producing in Brazil as Audi, BMW, Jaguar Land Rover, Chery, Foton, JAC Motors e Sinotruk. The remaining amount of US$ 20.0 billions investments are related to manufacturers already install in Brazil that plans to implement new assembly lines to increase their production capacity, modernization of facilities, production of engines and components, new vehicles projects, nationalization and development of new product and R&D and others. The planned investments and the period, as well as the majority participation of the enterprises. Only US$ 500 millions out of US$ 22.3 billions initially announced, representing 2%, are originated from Brazilian companies, as follow: Agrale, Volare e MMC Automotores do Brasil (Table 2) [START_REF][END_REF]. The program Inovar-Auto program provides that's the qualified companies could take advantages of taxes (IPI). On the other hand, assumed commitments under the current targets of the goals [13].

New Investments

Investments must be implemented to install new facilities and vehicle production plants or new projects to improve vehicle assembly lines already working in Brazil. The licensed enterprises must present their projects and after approval they must implement it. The enterprises may import similar vehicles to the ones that will be produced by the new facility during its construction and apply the IPI reduction, introducing the product to the market with similar conditions comparing to a future stage when the plant start the production locally. The enterprises must also present the information regarding the investment projects evolution. The legal acts issued after the initial proposal for the program have altered the targets of the program due to pressure of the selected enterprises, stripping the proposals of its original characteristics. Basically, it was influenced to become a public funding to finance private interests as tax relief. These resources are including in the companies budgets as investments. A diversity of scopes with no relevance to technological development were also aggregated in the program. In the following items are described the topics of the program if implemented it would enhance the national competitiveness for exportation, and it would also provide national research and development centers of expertize.

Energy Efficiency

Energy efficiency, for the present study, is understand as the autonomy of a vehicle in kilometer per liter units, or energy consumption represented in mega joules per kilometer (MJ/km) and these measures are made according to the methodology established by the legislation of the program. The licensed enterprises must reach the minimum target of 12.08% reduction according to the Federal Decree no 7819/2012. The current results are evaluated in specific periods during the license (Nov/16 -Oct/17).

Research and Development

The investments may be applied to basic research, applied research, experimental developments and technical support services. The enterprises must invest a percentage of their revenue in R&D, increasing from 0.15% in 2013 to 0.50% in 2017. This investment aims to improve technology and innovation of new products and processes in the country.

Engineering and Basic Industrial Technology

The enterprises licensed as manufacturer or importer may also invest their capital in engineering, basic industrial technology and suppliers' capacitation. These investments may be applied in engineering development, basic industrial technology, employees' capacitation, new products development, creation of new projects for laboratories and research, test tracks, development of machinery and suppliers' capacitation.

The minimum percentage of investments in engineering increases progressively from 0.50% in 2013 to 1.00% in 2017 of the revenue of the licensed enterprise.

This requirement aims to develop the technology and innovation of new products and productive processes. Complementary regulation to the program Inovar-Auto introduces concepts, orientations, models, requirements and methodologies to follow up the accordance of the enterprises to the requirements.

Manufacturing Stages

The licensed manufacturer must fulfill the minimum manufacturing stages, direct or indirect, regarding infrastructure and engineering. The manufacturing stages that must be conducted are: upholstery, welding, anti corrosive treatment and painting, plastic modeling, manufacture, gearbox manufacture, steering system and suspensions assemblage, electrical system assemblage, brake system and axis assemblage, chassis production or assemblage, assemblage, final checking, compatible tests and self infrastructure of laboratories to develop product tests, and others. At least 80% of the vehicles must fulfill the manufacturing stages, promoting the development of the national industry regarding productive capacity, fomenting the development of new suppliers to the manufacturing stages. The minimum amount o manufacturing stages rises from 8 in 2013 to 10 in 2017.

Labeling and Standard Vehicle

One of the specific objectives of the program is to increase the participation in the Labeling and Standard Vehicle Program (PBEV) conducted by INMETRO that aim to provide information regarding energetic performance of products contributing to consumer's decision.

Industry Sustainability

The suppliers of strategic inputs and machinery must inform in the Inovar-Auto Program Monitoring System the products provided to the licensed enterprises, including values and other characteristics. This information will provide knowledge about the automotive supply chain allowing the governmental institutions implementing policies to support the sector. The strategic inputs are: raw material, parts and components used to manufacture and aggregate in the vehicles; machinery and aggregate parts; upholstery and injection machinery and their parts. This objective is divided in two different targets:

Target 1 -The minimum of 700 suppliers registered in the Inovar-Auto Program Monitoring System until March/2015. This target considers the automotive supply chain in general (basic inputs, auto parts, tires, painting, etc.) and enterprises that are associated to the National Industry Union of Components to Automotive Vehicles (Sindipeças). It represents 85% of total sales to the Inovar-Auto licensed enterprises. Target 2 -Accordance of 95% of the supplier inputs and machinery.

Discussion and Conclusions

The program Inovar-Auto is contributing to the sustainable development of the automotive industry in Brazil. It has stimulating new plants as well as the modernization of the ones already producing, production of more modern vehicles, energy efficiency increase, investments in R&D and engineering, nationalization of industrial processes and more participation in the Labeling and Standard Vehicle Program (PEBV).

When comparing the Brazilian initiative to developed countries automotive industry it is possible to notice that these countries have the majority participation of the enterprises the mains suppliers. In Brazil, however, the industrial plants are exogenous and international dependent regarding both technology and investments.

The investments provided by the program Inovar-Auto are 98% from international majority participation, influencing the technology transfer to the automotive sector and limiting the sustainable development in Brazil. The technology is introduced and licensed and do not incorporate the learning process of the research and development, keeping the industries in a position of dependent buyer.

The program Inovar-Auto has financed international enterprises using public resources investing in their production. These resources should come from the enterprises as a plan to become more competitive maintaining their markets. The enterprises in a capitalism society must compete for profits and as a consequence assume the risks.

The innovation and implementation of the segments that bring technology and competitiveness to boost the national automotive industry is no longer contemplated in scope of program Inovar-Auto.

This research aimed to evaluate using indicator the progress of the Inovar-Auto Program. However, we identified several distortions between the initial proposal and the current program. Consequently, politics and enterprises are being investigated for frauds.

Table 1 .

 1 Relevant legislation to Inovar-Auto Legislation Relevant Law n o 12.715/2012 It releases the program to incentive the technological innovation and aggregation of the automotive supply chain. Law n o 12.996/2014 It alters the Law n o 12.715/2012. Decree n o 7.819/2012 It regulates the Law n o 12.715/2012. Decree n o 8.015/2013 It alters the Decree n o 7.819/2012. Decree n o 8.294/2014 It alters the Decree n o 7.819/2012. Act 106/2013 n o 7.819/2012. Decree n o 8.544/2015 It alters the Decree n o 7.819.

Table 2 .

 2 Investments of the automotive manufacturers working in Brazil (Source:[START_REF][END_REF])

	Manufacturers	Majority Participation US$ Billions Period
	Agrale	Brazilian	0.017	2014/2015
	FCA -Fiat Chrysler	Italian	4.167	2011/2014
	Ford	American	1.994	2011/2015
	General Motors	American	2.708	2014/2018
	Honda	Japanese	0.417	2013/2015
	Iveco	Italian	0.481	2012/2014
	MAN	German	0.417	2012/2016
	Mercedes-Benz	German	0.625	2014/2016
	MMC Automotores do Brasil	Brazilian	0.417	2011/2015
	Nissan	Japanese	1.083	2011/2014
	PSA Peugeot Citroën	French	1.542	2012/2015
	Renault	French	0.308	2014/2019
	Scania	German	0.417	2014/2024
	Toyota	Japanese	0.417	2012/2015
	Volare	Brazilian	0.015	2014/2015
	Volkswagen	German	4.167	2014/2018
	Volvo	Sweden	0.820	2013/2015
	Audi	German	0.183	2013/2015
	BMW	German	0.275	2012/2014
	BYD (Build Your Dreams)	Chinese	0.083	2014/2015
	Chery	Chinese	0.530	2012/2014
	Foton Aumark do Brasil	Chinese	0.142	2012/2016
	JAC Motors	Chinese	0.417	2011/2014
	Jaguar Land Rover	English	0.313	2013/2020
	Metro-Shacman	Chinese	0.167	2012/2014
	Sinotruk	Chinese	0.125	2014/2016
	Yunlihong Motors do Brasil	Chinese	0.075	2012/2015
	6 Targets of the Program Inovar-Auto


Wonder A L Alves
email: wonder@uni9.pro.br

Saulo D Santos
email: saulods@uni9.pro.br

Pedro H T Schimit
email: schimit@uni9.pro.br

Hierarchical Clustering Based on Reports Generated by Scriptlattes

Keywords: Lattes curriculum, Sucupira platform, Scriptlattes, Clustering, Hierarchical clustering

Scriptlattes has been used as an important tool to analyze a curriculum database of Brazilian researchers (Lattes curriculum). Such analysis enables a user generating reports for specific research field, knowledge area, graduate courses, and so forth. However, when users need a report of a Graduate Program, for instance, it is necessary to create subsets of information in order to run the script. Since each report needs a subset, in this paper we propose a hierarchical clustering method to categorize reports generated by Scriptlattes. Finally, experimental results show hierarchical clustering of a higher education institution, and approaches to stress such clustering.

Introduction

The growth of scientific community in the last decades created new issues to quantify the production, quality and innovation of research results. Besides the evaluation of researchers, institutes and countries concerning the research that has been done, keep a robust database of the activities and production is becoming crucial to manage the research properly. In this direction, several computational tools specific to the scientific community have been developed, including: social networks [START_REF] Kadriu | Discovering Value in Academic Social Networks: A Case Study in Re-searchGate[END_REF], institutional [START_REF] Lynch | Institutional Repositories: Essential Infrastructure for Scholarship in the Digital Age[END_REF] and patents [START_REF] Ernst | Patent Information for Strategic Technology Management[END_REF] repositories, curriculum platforms [START_REF] Fernández-Breis | A Semantic Platform for the Management of the Educative Curriculum[END_REF] and others [START_REF] Burns | Institutional Repositories: Exploration of Costs and Value[END_REF] [START_REF] Edgar | A Survey of Scholarly Journals using Open Journal Systems[END_REF].

In Brazil, it is practically mandatory that all researchers keep their Lattes curriculum updated. Created with effort from the National Counsel of Technological and Scientific Development (CNPq -Conselho Nacional de Desenvolvimento Científico e Tecnológico), Lattes platform allows that every curriculum is available online to public consultation [START_REF] Lane | Let's Make Science Metrics more Scientific[END_REF][START_REF] Mena-Chalco | ScriptLattes: An Open-source Knowledge Extraction System from the Lattes Platform[END_REF]. Therefore, if a researcher wants to apply to a position in an University, sure his Lattes will be consulted previously by the University commission. According to CNPq, the Lattes Platform exceeds 3 million Lattes curriculum, being 6.35% of PhDs, 10.85% of masters 27.69% of graduates, 16.18% of specialists, 35.54% other levels and 3.39% of Lattes curriculum that do not have the information [9].

Although the public information is individually available for each researcher, automatic compilation of data to generate reports concerning scientific production of a certain research group is not an easy task, and it is not provided by Lattes plataform. Regarding this problem, ScriptLattes has been created as an open source tool to make the information extraction easier. Given a group of researchers registered in the Lattes platform, ScriptLattes downloads the curriculums in html format, extracts the information of interest, eliminates redundancies and create reports [START_REF] Mena-Chalco | ScriptLattes: An Open-source Knowledge Extraction System from the Lattes Platform[END_REF]. It is important to remember that the Scriptlattes has been widely used by various studies in Brazil and the results so far have been of great value as can seen in [START_REF] Ferraz | A Utilizac ¸ão da Ferramenta Computacional Scriptlattes para Avaliac ¸ão das Competências em Pesquisa no Brasil[END_REF][START_REF] Ferraz | The use of Scriptlattes Tool for Extraction and On-line Availability of Academic Production from a Department of Stricto Sensu in Management[END_REF][START_REF] Giordano | Uso do Scriptlattes e Gephi na Análise da Colaborac ¸ão Científica[END_REF][START_REF] Nigro | Strategic Management of Research Productivity from Graduate Medicine Program by the use of Scriptsucupira Computational Tool[END_REF][START_REF] Mena-Chalco | Bibliometria e Cientometria: Reflexões Te óricas e Interfaces[END_REF][START_REF] Mena-Chalco | Brazilian Bibliometric Coauthorship Networks[END_REF][START_REF] Mena-Chalco | Towards Automatic Discovery of co-authorship Networks in the Brazilian Academic Areas[END_REF][START_REF] Perez-Cervantes | Towards a Quantitative Academic Internationalization Assessment of Brazilian Research Groups[END_REF][START_REF] Perez-Cervantes | Using link prediction to estimate the collaborative influence of researchers[END_REF].

Informations that can be collected by using ScriptLattes are, for instance, statistic descriptions and collaboration graphs. This collection of information of curriculums is performed globally for all dataset and then the Scriptlattes displays the report produced by HTML pages containing links between its pages. Further, Scriptlattes user can be interested in getting reports with different views of dataset, such as: specific research line, course, knowledge area and so forth. Each report needs a subset of the dataset (eg, segmenting the curriculum by some criteria) and a execution of the subset.

From this limitation of Scriptlattes, this paper proposes a method that use Scriptlattes functionality to categorize reports generated by Scriptlattes. Precisely, this categorization is modeled by elements of graph theory in which is constructed a partially ordered set that induces a hierarchy based on a categorization of the data. Thus, the nodes represent subsets of curriculum grouped by some criteria that associates them. Finally, running a Scriptlattes for each node, user has different views of the dataset with its own settings (subsets of curriculum and customizations in general).

This paper is organized as follows: Section ?? has definitions and properties about hierarchical clustering. In Section ??, the proposed method is described. Results and applications of the hierarchical clustering of a higher education institution are in Section ??. Finally, Section 5 has conclusions and future works.

Theoretical Background

Consider Cv a set of Lattes curriculum. In machine learning, we say that P is a clustering (partition) on the dataset Cv if and only if P containing n groups (subsets) S 1 , S 2 , ..., S n of Cv such that the following conditions hold:

1. The clustering P does not contain the empty set, i.e., ∅ P.

(1)

2. The union of the groups in P is equal to Cv, i.e., Cv =

S i ∈P S i . ( 2
)
3. The intersection of any two distinct groups in P is empty.

∀S i , S j ∈ P, S i S j ⇒ S i ∩ S j = ∅. (3)
In this paper, we denote that P(C) is the group S i ∈ P containing the Lattes curriculum C, i.e., P(C) = S i if and only if C ∈ S i . Thus, we define a binary relation finer than on the set of clusterings of Cv, as follows: for any two clustering P i and P j on Cv, we say that P i is finer than P j (and that P j is coarser than P i ) if and only if every group of P i is a subset of some group of P j , i.e., ∀C ∈ Cv, P i (C) ⊆ P j (C).

(4)

In this case, we say that P i is a refinement of a clustering P j and written as P i P j . More details see in [START_REF] Brualdi | Introductory Combinatorics[END_REF][START_REF] Newman | Elements of the Topology of Plane sets of Points[END_REF]. This relation on a subset T of clusterings of Cv constitutes a partially ordered set (poset) and thus, we can run a scriptlattes for each clustering T i ∈ T and presents them in a manner categorized by a hierarchy based on the Hasse diagram of poset (T , ). To illustrate this idea, consider the following example: let P Area , P Course and P ResearchLine partitions of Cv clustered by knowledge area, course and research line, respectively, in such a way to satisfy: Cv P ResearchLine P Course P Area {Cv}. Thus, we have: To build the hierarchy of clusterings T is employed the technique traditional of machine learning, called hierarchical clustering [START_REF] Duda | Pattern Classification[END_REF][START_REF] Friedman | The Elements of Statistical Learning[END_REF], described in Section 2.1.

-S i ∈ P Area is

Hierarchical Clustering

Hierarchy of clustering can offer more information about the structure of the curriculums in the dataset. With a hierarchy, the cluster of curriculums can be seen at different levels, i.e., from the bottom level where each curriculum forms an independent cluster (singleton clusters) to the top level with only one cluster containing all the curriculums. The hierarchical clustering involves creating clusterings that have a predetermined ordering from top to bottom. There are two traditional approach for construction hierarchical clustering [START_REF] Duda | Pattern Classification[END_REF][START_REF] Friedman | The Elements of Statistical Learning[END_REF], divisive and agglomerative:

-Divisive: In this method is assigned all of the curriculums to a single cluster and then partition the cluster to two least similar clusters. Finally, we proceed recursively on each cluster until there is one cluster for each curriculums. -Agglomerative: Initially, the set of all curriculum is considered to be a single cluster and then, recursively, is calculated the similarity (e.g., distance) between each of the clusterings and join the two most similar clusterings.

In order to build the Hierarchy of clustering, it is required to determine the (dis)similarity between each pair of clusterings using a distance function. The main methods used to measure the distance between the clusters are [START_REF] Duda | Pattern Classification[END_REF][START_REF] Friedman | The Elements of Statistical Learning[END_REF]:

1. Single Linkage: the distance between two clusters is defined as the shortest distance between two curriculum in each cluster, i.e.,

∀T i , T j ∈ T , D min (T i , T j ) = min{dist(C i , C j ) : C i ∈ T i , C j ∈ T j }. (5)
2. Complete Linkage: the distance between two clusters is defined as the longest distance between two curriculum in each cluster, i.e.,

∀T i , T j ∈ T , D max (T i , T j ) = max{dist(C i , C j ) : C i ∈ T i , C j ∈ T j }. (6)
3. Average Linkage: the distance between two clusters is defined as the average distance between each curriculum in one cluster to every curriculums in the other cluster.

∀T i , T j ∈ T , D avg (T i , T j ) = 1 |T i | × |T j | C i ∈T i C j ∈T j dist(C i , C j ). ( 7
)
Note that, the distance functions between clusterings need of a distance function between curriculums that is defined in Section ??.

Proposed Method

Hierarchical clustering allows the creation of a cluster tree, as mentioned previously. The tree is not a single set of clusters, but rather a multilevel hierarchy, where clusters at one level are joined as clusters at the next level. This allows adjustment of the grouping level most suitable for our pretensions. Therefore, it is necessary to build a distance function between the curriculum, that is used in the kernel of hierarchical clustering algorithms.

Consider Inf Field (C) the function that represents the value associated in a given field on the Lattes curriculum C ∈ Cv. For example, Inf Area (C) is the value associated the knowledge area of curriculum C. Thus, consider F a list of associated functions on the Lattes curriculums. Note that, F are informations that are associated in each row of dataset, which is built by using a file where each row contains: personal ID, name, list of associated informations. Table 1 has the structure of the dataset. The Sucupira platform is a management tool used by the Coordination for the Improvement of Higher Education Personnel (CAPES -Coordenac ¸ão de Aperfeic ¸oamento de Pessoal de Nível Superior). By using this platform, programs report their performance to the coordination annually and, at the end of each four-year period, while CAPES verify if they show minimum quality required for maintenance. Data is imported directly from the Lattes platform, and it refers to the scientific production of each of the professors belonging to the assessed course. the import, we need to perform a manual checking, since many information regarding the registration of the professors data as well as the scientific productivity may still be incomplete [START_REF] Nigro | Strategic Management of Research Productivity from Graduate Medicine Program by the use of Scriptsucupira Computational Tool[END_REF].

For this purpose, we construct a sequence of hierarchies (T 2013 , T 2014 , T 2015 , T 2016 , T 2013-2016 ), where each element of this sequence contains a hierarchy of clusterings configured to execute scriptlattes for a specific period. Moreover, the clusters formed by curriculums of a same course are configured with the Qualis of knowledge area. Once the hierarchies of clusterings (T 2013 , T 2014 , T 2015 , T 2016 , T 2013-2016 ) are build, we can visit each hierarchy of clusterings T Period and run a Scriptlattes for each level of them in T Period . Finally, the reports produced by Scriptlattes throughout hierarchies of clusterings are organized into a web page that can be accessed at link: https://db.tt/5JnRPH7e

Note that it is possible to make a thorough checking of the information to be submitted to Sucupira platform by using the hierarchies of clusterings based on reports generated by scriptlattes. It is worth remembering that the preliminary check of scientific productivity of each professor permits the identification of those who may have not achieved the goals set by the program, determined by CAPES. With this result, managers can improve research strategies in order to improve their production during the period of quadrennial, avoiding any unfortunate surprises when assessing the course. A further hierarchy of clustering without period setting can be seen in this link: https://db.tt/ZOxTXHiP

Conclusion and Future Works

In this paper, we proposed a method that makes use of the Scriptlattes to build a hierarchy of clusterings based on reports generated by scriptlattes. In this hierarchy, the nodes represent subsets of curriculum grouped by a criteria that associates them and Scriptlattes is executed for each node. The hierarchy of clusterings built provides more information about the structure of the curriculums in the dataset. Thereby, the cluster of curriculums can be seen at different levels, i.e., from the bottom level where each curriculum forms an independent cluster (singleton clusters) to the top level with only one cluster containing all the curriculums. It allows the Scriptlattes user to access different views on the reports generated from the dataset. Moreover, it has been presented a example of application for data extraction for Sucupira platform, which used the proposed hierarchy approach. As a future work, we intend to study the similarities between clustering on different hierarchies, and analyze the evolution of collaboration graph along the hierarchy of clusterings.

  the group of Cv belonging the knowledge area i; -S ij ∈ P Course is the group of S i ⊆ Cv belonging the course j of the knowledge area i; -S ijk ∈ P ResearchLine is the group of S ij ⊆ S i ⊆ Cv belonging the research line k of the course j of the knowledge area i. Therefore, T = P Area ∪ P Course ∪ P ResearchLine ∪ Cv. Fig. 1 shows part of a branch of the Hasse diagram (T , ).

Fig. 1 :

 1 Fig. 1: Example of part of a branch of the Hasse diagram (T , ).

  depending on the cluster height in the hierarchy we can provide different settings for Scriptlattes, allowing different treatment to clusterings by knowledge areas, courses, research lines and single curriculum.

Fig. 2 :

 2 Fig. 2: Hierarchical clustering dendrograms

Table 1 :

 1 Structure of the dataset

		Dataset
	Personal ID	Name	Inf Area	Inf Course	Inf ...
	Lattes ID of the person 1

person 1 ID of area 1 ID of course 1 ... Lattes ID of the person 2 person 2 ID of area 1 ID of course 1 ... Lattes ID of the person 3 person 3 ID of area 1 ID of course 2 ... Lattes ID of the person 4 person 4 ID of area 1 ID of course 2 ... Lattes ID of the person 5 person 5 ID of area 2 ID of course 3 ... Lattes ID of the person 6 person 6 ID of area 2 ID of course 4 ... Lattes ID of the person 7 person 7 ID of area 2 ID of course 4 ... Lattes ID of the person 8 person 8 ID of area 2 ID of course 4 ... Lattes ID of the person ... person ... ID of area ... ID of course ... ...

The distance function between curriculum is defined as following:

where ω k is a weight associated the function Inf k ∈ F . For example, the hierarchy of clusterings shown in Fig. 1 can be built using single linkage as the distance function between clusterings and the functions associated Inf Area , Inf Course and Inf ResearchLine also used to define the following distance function between curriculums:

where

Once the hierarchy of clusterings T is build, we can visit the clusters T i ∈ T (see Fig. 2) and associate each cluster S k ∈ T i the result of Scriptlattes. Moreover,


André Lira Muniz

Jair Debora Correa

Minoro Abe

Fábio Vieira

Do Amaral

Lauro H C Tomiatti

André Gomes De Lira Muniz

Debora Adriana

Jair Mões Correa

Fábio Vieira Do Amaral

Mitigating Serialization and Traceability, a Study on the Strategies for the Implementation of the System and Adaptation to the TBR n o . 54 2013

Keywords: Paraconsistent Logic Annotated Evidential Et, , Traceability, WHO

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

The improvement program, of the regulatory process of The Brazillian Health Regulatory Agency (Anvisa), established by Decree n o . 422 of April 16, 2008, and also the provisions of Law n o . 11,903, of January 14, 2009, it provides for the implementation of the national system of drug control and the mechanisms and procedures for tracking drugs in the chain of pharmaceutical products; practice that determines the new guidelines and unique identification rules for drug being called UIR. This resolution is based on the concept of serialization and traceability, Despite widely publicized by the media Brazilian society did not absorb all the concepts involved. Some questions have not been September permanently. When measured technological solutions to a subject, there are several options in both the national and international market, however, there is great difficulty in understanding the new resolution in terms of understanding the standard, as well as the concepts of serialization and traceability which makes complex close the process to implement the solution throughout the chain so that the solution is unique and the data can bring all necessary information at all stages of the selection of raw materials, production, marketing to the end consumer.

This work seeks to demonstrate macro form the concept, methodology, and application with the technological solutions that have been used in Brazil. It is noteworthy that this study has as main objective the drug developers.

Theoretical Background

Information Technology

To Santos [START_REF] Santos | Gestão de Farmácia Hospitalar[END_REF] using information technology when it comes to health is fundamental prioritize therefore can often be a fine line between over-experience of fatality. In the Industry of Health, there is always an attempt to cut public spending and demand greater efficiency in this industry, several companies associated with the health as the American Hospital Association, the Health Industry Business Communication Council, the National Wholesale Druggists Association, among others, invest in research called Efficient Healthcare Consumer Response. In this research, a strong recommendation is to implement information systems to automate the current processes of the supply chain [START_REF] Ching | Gestão de Estoques na Cadeia de Logística Integrada Supply Chain[END_REF].

The best way to promote the performance of the supply chain, while in parallel, control is the short-term costs, not to colortar budgets, expenses, but invest in process improvements, and technological resources, which will eliminate costs of supply chain [START_REF] Ching | Gestão de Estoques na Cadeia de Logística Integrada Supply Chain[END_REF].

To Taraboulsi [START_REF] Taraboulsi | Administração de Hotelaria Hospitalar[END_REF] it is essential that health institutions have as a tool management systems provided by IT, because that enhance the processes of treatment, spread and transfer of information, add value to serve vices and make decisionmaking more agile, effective and consistent.

Holland and Nimno [START_REF] Holland | Transitions, Part 1: Beyond Pharmaceutical Care[END_REF] report that hospital pharmacies were incorporating advanced technological resources with computerized prescription, automation system for distribution of drugs and computerization processes.

According to Gomes and Reis [START_REF] De Magalhães Gomes | Ciências Farmacêuticas: Uma Abordagem em Farmácia Hospitalar[END_REF], computer automation as acts as an important tool for rationalization of use of time and agility of activities in the pharmacy.

Tecnologies Used for Product Traceabilitys

Bar codes to a use widely disseminated. Used in various industries was initially used in the retail market and therefore, widely disseminated in markets. Barcodes have a lot of information and graphs numeric and alphanumeric data. This encoding has intervals of diffuse reflectivity alternating, are represented by rectangles, however, no information, but certainly make typing easier [START_REF] Swartz | Fundamentals of Bar Code Information Theory[END_REF]. The GS1 System is based on bar codes and is the global standard used, presenting the data layout to be followed:

-EAN/UPC Universal Product Code, that is widely used in point of sale (POS) and have an agility in capturing information; -DataBar: This code family can be used in POS (point of sale), but has a smaller size and has the capacity to have more information than EAN/UPC. -Code 128: Standard Code of GS1 keys. This pattern should not be used for identification at the POS; -ITF-14 (Interleaved Two of Five): This standard should not be used for identification at the POS; It can be printed on cardboard; -Data Matrix: It has a higher storage capacity being a symbol it with greater capacity than that linear codes.

Table 1 shows a comparison of the technologies used for product traceability, which highlights its main use factors. Through the table is possible to verify that the Radio-Frequency Identification Technology -RFID, the principle is the most suitable for traceability because medicines, among other factors, the minimum data manipulation, which gives security to the supervisory body and its wide range in the distance data capture, which increases safety and mapping process, being able to control not only their location in real time, but act quickly if the exit load predefined script and can avoid the theft of the same [START_REF] Metzner | Modelo de Rastreabilidade de Medicamentos Utilizando Identificação por Radiofrequência, Redes de Sensores Sem Fio e o Conceito de Internet das Coisas[END_REF].

Understand Serialization and Traceability of Medicines

We can divide the process of serialization and traceability in two stages that are serialization and aggregation. In designing serialization, it happens in the coding phase, because at this time are entered the data that references all information as batch identification, expiration dates and the dates and the details of the label and the definition of data [8]. In other words, the serialization is the definition and implementation of a unique identifier, such as a serial number that identifies the individual packages of medicines, your application is through the code printing (2D) and production batch data.

It is important to keep the information in unit doses or rather the lower marketed dose. For this and crucial that printing equipment can print the information in the Data Matrix format, this standard is defined and regulated by ANVISA, such code have the serial number, product registration number, batch, manufacturing and expiry dates that have quality standard [8]. In order to check the printed information, see the example in Figure 1, the serialization equipment needs of visual inspection systems as well as waste efficient and analyzing the printed data evaluating and making sure they are within the minimum criteria set out in the DRC Standard n o . 54 2013 in order to be accepted. The requirements are [8]:

-Standard print size.

-Comparison and analysis of the data reported by the ERP system with the label. -Quality Printing.

-Process analysis and in case of failure in print or evidence of divergence in the data printed a reject process should be established. Standard print size.

Aggregation

When measured aggregation of drugs, it occurs after the codification of the serialization information, medications that have been identified in photographic form containing the data of aggregates cartridges rows and the data to be easily identifiable to get information regarding the composition , origin and storage.

It is important that a label is printed after closing the box when it is complete. The box must have a label that will be unit must be aggregated into a single shipment box so to have a single record doing the same family or group [8].

The shipping box should be inspected and it is important to have the printed record by the system and will have the information of the whole makeup box, and constitute a new code. This new label "father" must be fixed in the shipment box to identify the "children" [8]. The TBR n o . 54 of 2013 does not have a mandatory requirement regarding the aggregation of shipping boxes on the pallet, however, to be effective control and traceability during all stages of the process is required data to be stored and sent to the server traceability of the manufacturer and stored in a database for later to take effect the transmission of information to ANVISA where there will also be storage in a database.

For this to happen in a way that facilitates the control of the physical location is important that shipping boxes have an identification number and can easily get the information inspected, and that the place of storage, to be easily identified. So that the process can be completed, after collecting boarding box data and validation of them will require a new label is printed with all units of parents and children and this information should be in a visible place, after "stretching" or "strecht wrap" (placement strectch film) to protect the packing boxes to be sent to the logistics operator.

Definition of the Production Line

In the consignment of production data step is defined to be included in Datamatrix, such as the data of separation of raw material, weighing the production of semifinished data, reconciliation, release, among other information related to production.

For this phase of the process it is necessary to define a unique serial number for each product unit and for this serial also used the registry number of the product at ANVISA, including batch number, expiry and manufacturing dates

Methodology

This paper can be considered an exploratory study to generate a structure that will subsequently be tested in future studies, through the development of hypotheses to be investigated; descriptive, by engaging the attempt to control and manipulation of variables; case study, to be returned to the depth, targeting a full contextual analysis of a few facts; and laboratory research, because it was not applied yet [START_REF] Bowersox | Supply Chain Logistics Management[END_REF].

Initially, there was a survey of macro use of technology in the drug supply chain, using materials such as articles published in scientific journals and international very important events. Then we made a study of the methods and drug traceability technologies used in Brazil and the world, and its effectiveness in relation to the following requirements: guarantee information along the supply chain, decrease in counterfeit drugs, traceability lot quickly, with quality that reaches the end customer and information available on the medicine for it.

Based on this knowledge, it concluded the elaboration of cover the reader ways to mitigate serialization and traceability, through a study on strategies for system implementation and adaptation to the TBR n o 54, 2013. An attempt to improve the existing process and identify future research possibilities.

Results and Discussion

The new tracking law until the end of 2016 the entire pharmaceutical industry should follow the new rules. The proposal is that the production stage to consumption registration is made, storage and transmission of data. To provide greater security is being adopted this global trend.

Clearly there will be the expansion of the security when the traceability process is being used for medicinal products. This is a good practice and is also a trend in other countries that are seeking to increase the safety of medicinal products. Avoiding not only fraud, robbery of cargo it, but also providing greater security and protection to the consumer.

In the productive sector, it is the measure will allow the greatest control of all costs of the stages of production and logistics. The process and all the production and distribution chain links are essential for any drug traceability process to work. The links found pharmacies are one of the distribution links that need to inform the reception of this, during the delivery, the submission processes and anomalous situations, such as loss and falsification, the manufacturer of the drug, and the previous link in the supply chain. All existing connection in the chain has responsibility with the pharmaceutical laboratory that all stages of the delivery process until the sale can provide the information to ANVISA the repository of records of the manufacturer's traceability of events.

To protect consumers may be noted that traceability enables more secure and reliable buyers in the product they are buying. There will also be a feature of industries and government to manage health care costs and be more easily and efficiently, and regulators can monitor more effectively.

Conclusions

Traceability of medicines has not been standardized in the world, and that we still have large amounts of counterfeit drugs, which pose a safety hazard to the final consumer, therefore this product without origin does not have the necessary quality.

Traceability of drugs is no longer a competitive factor, but a necessity to get the safety of the product to the end consumer. For the traceability process is accepted, it is necessary that the existing steps are met, the change is planned and the use of appropriate technologies enabling assurance and tracking of the drug to its ultimate destination, and thus its quality, reducing cases of counterfeit medicines and providing a response and faster action, if necessary to withdraw a circulating drug. In that it contributes to the reverse logistics of these products, enabling the sustainability of the process.

Mitigating

  Serialization and Traceability, a Study on the Strategies for the Implementation of the System and Adaptation to the TBR n o 54 2013 1 Introduction

Fig. 1 .

 1 Fig. 1. Printer of datamatrix

Fig. 2 .

 2 Fig. 2. Label aggregation (Source:[8])

Fig. 3 .

 3 Fig. 3. Example of a two-dimensional code (2D) of the DataMatrix [12]

Table 1 .

 1 Comparison of different Traceability technologies (Source:[START_REF] Metzner | Modelo de Rastreabilidade de Medicamentos Utilizando Identificação por Radiofrequência, Redes de Sensores Sem Fio e o Conceito de Internet das Coisas[END_REF])

		Bar Code	QR Code	RFID
	Storage capacity	Low	High	High
	Reading Device Di-	Only Infrared	Mobile camera appli-	Mobile NFC and spe-
	versity		cation to read QR	cific application and
			Code	systems with anten-
				nas that have a soft-
				ware
	Reading need to line	Yes	Yes	Yes
	of sight
	Distance for informa-	Small	Small	Far
	tion capture
	Safety Data	High, there may be	High, there may be	Minimum,	cap-
		change image	amendments image	ture and send data
				without intervention


Caique Z Kirilo

Jair M Abe

Luiz Lozano

Renato H Parreira
email: renato@paradecision.com

Eduardo P Dacorso

Using Logic Concepts on Six Sigma

Keywords: Decision-making, Six sigma, Quality, Paraconsistent Annotated Evidential Logic Eτ

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

Introduction

This paper proposes an improvement on the Six Sigma concept by reducing the human factor risk causes by the misallocation of human resources for the execution of tasks or the misapplication of the DMAIC method. The proposed is a method based on an expert system Paraconsistent Annotated Evidential Logic Eτ . Such system identifies inconsistencies in the decisions taken by experts in the program, making possible to deal with these inconsistencies and, also to identify if the experts have the necessary knowledge to take the right decision. Six Sigma is a process based entirely on the human factor, so applying an artificial intelligence will minimize errors caused by it making Lean Six Sigma stronger and more efficient, empowering the process of quality improvement.

We can best exemplify the idea as follows: imagine many managers and employees participating in a brainstorm where the goal is to create a cause and effect diagram for a particular problem, in that meeting will be people from different hierarchies and influence, then if we want to get the most reliable results in this brainstorm we need to shield the environment so that factors such as appearance, influence or intimidation will not interfere in the decision-making process.

Integrating paraconsistent logic in the creation of this cause and effect diagram through software is a solution to make the environment that is happening brainstorm get as close as possible to neutrality. In that way participants will register their opinions transparently and totally focused on the problem, thus obtaining more accurate results.

Six Sigma -Backgrounds

Based on studies of Werkema [START_REF] Werkema | Criando a Cultura Seis Sigma[END_REF], Lean Six Sigma is a quantitative management strategy starting from the number of faults in the production or product process. It aims to improve them to increase customer satisfaction and generate a higher profit margin. It must be implemented "top-down" and all employees, regardless of their segment or hierarchy, should be part and have knowledge about the program. Each of them will have responsibilities and tasks in order to have a good Lean Six Sigma implementation. Each employee assumes a position and respective responsibilities described below:

-Sponsor of Lean Six Sigma: This hierarchy is respected when Paraconsistet Logic is applied to these concepts.

The DMAIC Method in Six Sigma

One of the Lean Six Sigma infrastructure elements is the establishment of teams to execute projects that strongly contribute to the achievement of strategic goals of the company. The development of these projects is carried out based on a method called DMAIC [START_REF] Werkema | Métodos PDCA e DMAIC e suas Ferramentas Analíticas[END_REF]. The DMAIC method consists of 5 steps, Define, Measure, Analyze, Improve and Control.

-D -Define: Define the precise scope of the project.

-M -Measure: Determine the location or focus of the problem.

-A -Analyze: To determine the causes of each priority problem.

-I -Improve: To develop, evaluate and implement solutions for each priority problem. -C -Control: To ensure that the scope of the long-term goal is maintained.

Human Errors in Six Sigma

No doubt this is the most sensitive part of Six Sigma, the people who are responsible to make it work are the same that causes its fail. Weighing it [START_REF] Werkema | Perguntas e Respostas sobre o Lean Seis Sigma[END_REF] addressed this issue based on the studies of Schmidt [START_REF] Schmidt | Fundamentos de Auditoria de Sistemas[END_REF] and the result was a list of most significant factors involving human error. The Paraconsistent Logic has the intention to minimize or eliminate the negative impacts caused by these factors.

Misinterpretation: To ensure uniform interpretation of the words is necessary to provide precise definitions, plus auxiliary tools such as checklists and examples. They should also be given detailed information and examples of how to calculate, summarize, record, etc. On critical issues, should provide formal training, along with tests to check the "capacity" of candidates for sensors on the process [START_REF] Werkema | Perguntas e Respostas sobre o Lean Seis Sigma[END_REF].

Inadvertent error: Inadvertent error is unintentional, unpredictable and often unconscious, that is, the person who makes the mistake is not, then, conscious of having committed it. The data produced by an inadvertent error has a random characteristic, which is useful for identifying errors of this type. The choice of solution for this type of error is somewhat limited because the root cause of inadvertent mistakes is an inherent weakness in the human been, so to say, the inability to keep an eye indefinitely [START_REF] Werkema | Perguntas e Respostas sobre o Lean Seis Sigma[END_REF].

Lack of technique: The error for lack of technique is the result of incomplete knowledge by the human sensor. Some people have developed a more skillful way -some kind of "trick", i.e. a small difference in the method that represents a big difference in the results. Those who know the "trick" get superior results; others, not. The solution in this case is to study the methods used both by those who have superior performance, as for those that have underperformed. These studies have identified the "tricks" that can then be transferred to all employees through training or embedded technology [START_REF] Werkema | Perguntas e Respostas sobre o Lean Seis Sigma[END_REF].

Conscious error: The conscious mistake is intentional. The person who made it is aware of that, and intends to continue, often as a form of defense against real or imagined injustices [START_REF] Werkema | Perguntas e Respostas sobre o Lean Seis Sigma[END_REF].

Dissimulation: Dissimulation is a deliberate alteration of data collected for a variety of usually selfish purposes: reducing workload, escape from unpleasant tasks, self-promotion, fear of being punished for delivering bad news. The reduction of dissimulation can be achieved in part by the establishment of an environment that adopts open communication, which requires leadership by example, senior management [START_REF] Werkema | Perguntas e Respostas sobre o Lean Seis Sigma[END_REF].

Distortion: Distortion and dissimulation are similar, but there are subtle differences. In dissimulation the human sensor knows the facts and alters consciously. The distortion is not necessarily consciously, the possible existence of interior forces influencing the human sensor response (e.g., fixed ideas due to the habit). The distortion can even be results from the human sensations and feelings. An example is the test conducted by a razor blade manufacturer, in which the reports of the employees who did the test were distorted because they knew the number of beards already made with the blade being tested [START_REF] Werkema | Perguntas e Respostas sobre o Lean Seis Sigma[END_REF].

Uselessness: The feeling of worthlessness is another source of conscious error. If the employees find out that their reports do not lead to anything, they stop making them. The situation is even worse if workers find that their reward for acting as sensors is an unjustified guilt [START_REF] Werkema | Perguntas e Respostas sobre o Lean Seis Sigma[END_REF].

An Expert System Based on Paraconsistent Logic

Studies based on [START_REF] Carvalho | Aplicação de Lógica Paraconsistente Anotada em Tomadas de Decisão na Engenharia de Produção[END_REF], a synthesized form of PDM, a support method in the decision-making process based on Paraconsistent Logic, which uses the experts' experience to check the feasibility or unfeasibility of a given situation.

From an initial issue called proposition, factors that impact the feasibility or unfeasibility of the matter must be determined. These factors can be divided into sections that are analyzed in order to extract the most of the experience from the specialists.

To make a feasibility analysis of an enterprise for decision making, planning is under the coordination of a particular person (the entrepreneur himself, an engineer, a consultant etc.). This person works the data in a way to translate them for the language of Eτ logic. This will be called expert knowledge engineer (CE) [START_REF] Carvalho | Aplicação de Lógica Paraconsistente Anotada em Tomadas de Decisão na Engenharia de Produção[END_REF].

According to [START_REF] Abe | Introduction to Annotated Logics: Foundations for Paracomplete and Paraconsistent Reasoning[END_REF] the Paracon-sistent Decision-Making Method has 8 steps:

1. To set the level of demand of the decision whether to take. 2. Select the most important factors and most influential in the decision.

3. Establish the sections for each of the factors, if necessary. The quantity of sections can be chosen depending on the desired granularity/precision. 4. Build the database, which consists of the weights assigned to the factors (When necessary to distinguish them by importance) and the values of favorable evidence (or degree of belief) (a) and contrary evidence (or degree of disbelief) (b) assigned to each factor-sections combination. The weights and the evidence values are assigned by experts chosen conveniently. The database may also be built with stored statistical data obtained from previous experience in performing similar undertakings. 5. Do field research (or data collection) to check, in this case, where section (condition) each factor is. 6. Get the value of the favorable evidence (a i,R ) and the value of the evidence against (b i,R ) resulting, with 1 ≤ i ≤ n, for each of the factors (F i ) chosen. The sections found in the search (S pj ) by application of the techniques of maximization (operator MAX) and minimizing (MIN operator) of Eτ logic. 7. Get the degree of favorable evidence (a w ) and the unfavorable evidence (b w ) of global analysis of the points representing the factors chosen in the lattice τ 8. Making the decision, applying the decision rule or algorithm para-analyzer.

Unifying Concepts

Unifying the concepts of Paraconsistent Logic with Six Sigma is relatively simple; it is possible to draw an equivalence between these two issues.

Paraconsistent Logic has a role of knowledge engineer, who will be responsible for assigning and coordinating the specialists' tasks. The Lean Six Sigma Sponsor will play that role. As he/she is the person who has the macro view of the company, however has access to and power over the micro views.

Other specialists will perform different tasks as described in Chapter 2 of this paper, these experts according to Paraconsistent Logic can have certain weight in decision-making, this weight is set according to the degree of experience that the expert has with the issue at hand. For example, a Green Belt can opine better on a particular issue than the Black Belt due to have more operational knowledge, as the Black Belt has more management experience.

The experts opine on predetermined tasks, stipulated by the Lean Six Sigma Sponsor. He/She will play the role of the knowledge engineer and will split the task on several factors, which will be investigated by all experts. Thus experience of all members will be utilized optimally. The contradictions will be canceled by PDM, making the whole process more effective. Following is illustrated the union of concepts. The decision is made upon certain factors, shown in Figure 1. The factors are split into sections to better specify function the issue being dealt. That is, the issue to be addressed is thoroughly analyzed before being discussed, and when discussed will be extensively analyzed.

Figure 2 shows a fictitious example of how you deploy a part of the six sigma in paraconsistent logic. The program members will respond to certain factors with a percentage of certainty and uncertainty, and then the logic will do the calculations that will eliminate the contradictions.

This way the human error causes can be eliminated as the tasks will be extensively treated during its course, so, before been executed. It is also possible to ensure that all program members effectively understand the importance of a particular task. Figure 3 shows how it can be made the integration between the experts of Six Sigma and paraconsistent logic. The weights assigned to the experts will impact the decision-making, then in certain situations these weights can be changed according to the greater knowledge of the expert in question. This paper, though bring a more superficial view of the subject, invites the reader to reflect on the use of paraconsistent logic as a way to improve the implementation of Six Sigma and mitigate their vulnerabilities.

It is possible with the use of an artificial intelligence minimize human errors that put at risk the program. The intention was never eliminated the human's deci-sion-making process; on the contrary, the intention is to improve the experience of the human being and makes it less susceptible to failures throughout the process.

Fig. 1 .

 1 Fig. 1. The MPD concept

Fig. 2 .Fig. 3 .

 23 Fig. 2. The Union of Concepts

Fig. 4 .

 4 Fig. 4. Difference between two ways of making decisions

  The person with the highest executive level in the company, responsible for defining all the factors necessary for the implementation of the program. -Sponsor Facilitator: It is one of the company directors. It has the function of advising the Lean Six Sigma Sponsor in implementing the program. -Champions: are directors or managers of the company who is responsible for supporting the projects and remove difficulties for its development. -Master Black Belts: They are professionals who advise the Sponsors and Champions, which must have great ability to teach and act as mentors for Black Belts and Green Belts. -Black Belts: They are team leaders, whose function is to coordinate projects.

	Must have a high technical knowledge and a number of qualities that char-
	acterize as being able to perform this function.
	-Green Belts: They are members of teams led by Black Belts or leading
	teams in conducting functional designs.
	-Yellow Belts: They are usually supervisors, properly educated and trained
	to understand the basics of the program. It has the function of supervising
	the program is well implemented across the organization and run projects
	focused on development.

-White Belts: They are professionals operating company level, properly educated and trained in the program. They have the function to support the Green Belts and Black Belts.