Ralf Kretschmer
email: ralf.kretschmer@miele.de

Stefan Rulhoff
email: stefan.rulhoff@prostep.com

Josip Stjepandic
email: josip.stjepandic@opendesc.com

Prospective Evaluation of Assembly Work Content and Costs in Series Production

Keywords: Product Realization, Manufacturing, Digital Factory, Assembly, Process Planning, Data Mining

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

INTRODUCTION

Today globally operating companies face additional challenges due to the increasing variability of products and complexity of processes. Therefore there are growing demands on the flexibility in the production system on the economic dispatch of new products in an existing production line. In the modern product emergence process production planning gets increasingly important and has to be executed in parallel to the product development [START_REF] Bracht | The Digital Factory between vision and reality[END_REF]. In this early phase of the product creation a first start for planning processes is a cost calculation for the industrialization of the product in existing production lines regarding basic conditions [START_REF] Bley | Integration of Product Design and Assembly Planning in the Digital Factory[END_REF]. The economic feasibility of series production must be assured with vague information on the product and given general conditions, e.g. shift model. This is a great challenge especially to the planning of the cost-intensive assembly of the product.

In order to meet this challenge PROSTEP AG supports Miele & Cie. KG, one of the leading manufacturers of domestic appliances, developing innovative methods in the research project ProMondi. Aim of this project is the accurate estimation of the expected assembly work content and the resulting costs in an early stage of the product development as well as the additional support of the design process with assembly knowledge for the specific design. The approach contains the usage of existing plan-ning data in order to extrapolate assembly processes. Especially linked product and process data allow the innovative usage of Data Mining methods. New processes appropriate to assemble the given new product shall be designed based on this existing linked product and process data. Automatic analysis with a specific Data Mining model can be used to create a first draft of the assembly process and estimate the expected costs. Additional use cases can be addressed. Following production planning processes can be supported by automatic proposals of adequate assembly processes, which then can be customized. Moreover the design engineer can be supported at the selection of appropriate joining elements. With this approach an assembly knowledge based support of the designer in series production can be achieved using innovative data mining methods.

USE CASES MIELE

In order to address the challenges of data mining the integration of various planning tasks within the PEP, new concepts are necessary. Though, as a part of integrated product and process development there are different definitions for various phases and aspects of planning activities along the PEP. Regardless of the specific definition of these phases and aspects, however, based on the analysis it is certain that great amount of their containing information and knowledge are either utilized insufficiently and ineffectively or remain unused [START_REF] Erohin | Intelligent Utilisation of Digital Databases for Assembly Time Determination in Early Phases of Product Emergence[END_REF]. In this regard, the presented concept focuses on product design and production assembly planning. Subsequently, for the product designer and production planer, there are varieties of applications, which can assist the design or the planning process through information gathered by data mining.

Enrich CAD data with assembling information: Derived from similar previously constructed products assembly information such as time data about the actual design situation can be identified and provided in order to support the designer. These additional information can be used to enrich the CAD data to support the current design and be updated in later assembly planning processes.

Suggesting assembly connections:

An assisting option for the designer is a suggestion list of similar previously constructed assembly connection variations. These lists give a quick overview of possible and already implemented connection types in the assembly.

Assembly process estimation:

The focus is on the creation of an assembly process for a new product. Based on existing product and process data compilation of a first approximated assembly process for a new product could be developed. From this, the production planner can specify further details and thus determine a first estimation regarding assembly time. Based on the assembly time and associated calculation scheme, the planner can perform the first cost estimation in a very early planning phase.

The information in production planning and engineering processes can mutually enrich each other. Additionally intelligent interconnecting information from both areas creates added value. The newly obtained information supports the workflow throughout the PEP. Therefore, as part of this concept some requirements need to be met. Thus the pre-conditions attached to both systems as well as their respective processes have to be fulfilled [START_REF] Schallow | Application Protocols for Standardising of Processes and Data in Digital Manufacturing[END_REF].

Data Mining methods can be used for data clustering and classification, however criteria for comparison of data sets have to be identified [START_REF] Han | Data Mining : Concepts and Techniques[END_REF]. To determine these criteria, within the scope of ProMondi project, a survey of users as well as an analysis of various tools of the DM was performed. The objective of this analysis was to identify attributes relevant for assembly processes that could be assigned to products and parts in CAD [START_REF] Hartung | Moderne Produktionsplanung -Integration in der Produktentstehung[END_REF], PDM and production planning systems. In CAD systems attributes assigned to parts contain mainly geometric information including volume and weight. The PDM systems contain organizational information, such as creator, version and revision as well as the mentioned parts information form CAD [START_REF] Eigner | Product Lifecycle Management -Ein Leitfaden für Product Development und Life Cycle Management[END_REF]. In addition to the conventional systems for design and stacking product parts and assemblies, systems for process planning and time measurement were also taken into account. They sustain a comprehensive portfolio of information and therefore can be used to distinguish different product parts and assemblies. The results of this analysing are capsulated as an object oriented data model, further described in chapter 3.

The necessary enrichment of product and process data on the fly for the presented concept requires additional efforts in the design. This additional expenditure also relates to the assembly connections and includes the acquisition of new information form the designer's know how. The designer usually defines assembly connections either implicitly through formed locked joints by the shaping of the parts or explicitly by connecting elements such as in screwed fasteners.

The designer of the assembly connection considers all these information in the design but cannot store them in the CAD model because the CAD tools for the most part are not able to define the necessary attributes.

To overcome this problem as part of the concept presented in this paper, the designer will be provided with an additional tool in the CAD system. It can be used to create assembly connections and gives additional information and explicit design possibilities. These additional assembly information are named below as "product assembly information". Thus, data will be collected in the source system, the CAD system in particular. Since the defined objects are not part of PDM systems an extension is necessary in order to implement connections as objects and to store them after the transfer in the PDM system persistently. In the further processing, the product information will be linked to the planning processes. Unless the storage of product data are in the same system as for production planning, the information flow from the PDM system to the planning system as well as the Data Mining tool, for further analysis, has to be ensured.

In current planning systems often direct linking of processes to products is possible [START_REF] Petzelt | Anwendungsspezifische Datenmodelle in der Digitalen Fabrik[END_REF]. Thus an allocation of to be assembled product and the associated assembly processes can be realized. In the assembly, however, parts are joined with other parts or product. These assembly connections with their additional information have no digital equivalent object yet. However by means of an object such as the "product assembly information" it is possible to store useful additional connection information, which relates directly to the respective assembly connection. As part of this concept, the combination of the products and processes does not take place directly but through this object "product assembly information". The linking of product and process does not necessarily need to occur at the part level.

CONCEPT

The concept presented in this paper describes an assisting workflow to support the designer (Figure 1). As part of a new or modified design the designer creates new product data. In creating the assembly connections a software assistant supports the designer and enriches the CAD model with product assembly information for each connection. This product assembly information includes additional connection information including e.g. the torque screwed fasteners or the type and the form of a welded joint and information about other connection types. In the on going design process the designer can trigger an evaluation regarding the assembly connections in the model. For this purpose, the characteristics of the CAD model are first prepared and analysed with Data Mining. The analysis focuses on the product assembly information and their properties. The parts associated with the product assembly information and their geometric properties, are also included in the analysis as additional information set. Furthermore, an extended database is also provided and consists of product and process data of existing products, which are linked via the product assembly information. The characteristics of the product assembly information of the new product are compared with the properties of the product assembly information of the existing product in the extended database. Then the most similar product assembly information is determined from the existing products. This analysis can be restricted by a class of the connection types (screwed, weld, rivet) or deliberately left open to widen the solution space and to provide the designer with information about other assembly connections.

A limitation on the particular type of connection yields as a result of the closest realized assembly connection of the same kind. Depending on the properties of the parts, other mounting connections can also be found and proposed to the designer in a proposal list. The presented application for the support of the design process uses the product assembly information identified in the analysis of the PDM database to determine the respective associated and related sub processes. Each product assembly information represents an assembly connection. By multiple connections within the assemblies multiple sub-processes for the assembly can be determined. These processes contain the time data relevant for the new product design. Therefore the corresponding time information of the existing products and if requested an alternative proposal list is transferred in the CAD System and displayed. This assembly time information of the existing product represents a first approximated assembly time for the new product. So the designer is provided with this additional information regarding the assembly time and with an enterprise specific factor the corresponding cost of the current design solution. In the final step the designer is able to optimize the product iteratively on the base of anticipated assembly time and costs for each design.

Based on determined assembly characteristics a range of attributes is derived to classify the assembly of the parts. Figure 2 shows an overview of the generated data model for the data mining analysis.

The ProductAssemblyInformation (PAI) is the central element in this data scheme and represents the assembly of the product parts. References for time analysis, assembly requirements, designed parts or products as well as a wide range of meta data including the assembly department and other information are lodged. This element is supplemented with attributes of different connection types (see Figure 2).

Further connection types can be added to the data model. To provide the required information for the time analysis a standardized data model is applied. In this regard, ADiFa project's "Application-specific data models", so called ADiFa Application Protocols, were used, which offer the integration of processes and data for different DM systems [START_REF] Petzelt | Anwendungsspezifische Datenmodelle in der Digitalen Fabrik[END_REF].

The second fundamental object in the data model is the Item. It contains references to existing sub-assembly units, geometrical characteristics as well as ProductAssem-blyInformation. Each Item refers to the ProductAssemblyInformation, which also refers to further used Items. This construct is chosen to enable Data Mining methods to determine exact similarities between new parts and/or products and other existing parts. Furthermore, it makes comparison parts and products the new and existing ones, in any order and combination interchangeably possible.

In the first approach the attributes for screw connections are clustered and evaluated regarding the relevance for assembly operation. Figure 3 shows the identified attributes classified in the categories fasteners, installation / assembly situation, tools / equipment, installation regulations and additional assembly elements. These attributes are represented in the data model in different object classes here illustrated by colour. The evaluation regarding the influence on the assembly time provides a first indication for the relevance in the data mining analysis. Which attributes really are significant for the similarity of assembly connection have to be determined in a data mining analysis with a large quantity of product data.

Not all of these attributes can be identified in the mechanical design in the CAD system. Some can be determined in production planning workshops in order to optimizes the current design. Experienced designers can preallocate some parameters with estimated values which can be reviewed later. Other parameter and the corresponding value data can be extracted out of other systems e.g. the attributes of standard parts.

After aggregating and appending the data subsets from different sources and systems, it is necessary to remove redundant data sets [START_REF] Ohno-Machado | Improving Machine Learning Performance by Removing Redundant Cases in Medical Data Sets[END_REF] for the data mining process. The next step is converting and porting data in the presented data model. Depending on data source the conversion is either fully automated or partially automated with further manual adjustment. Often value and scale of different attributes are often heterogeneous. In these cases a normalization of ratings prevents the undesired high or low impact of certain attributes on the results and evaluation process. In this regard a [0, 1] linear normalization has been used. Additionally, a further attribute prioritizing via weighting can be necessary to define the importance of each attribute for the evaluation. An automated learning of the weights via machine learning methods depends on the existing data sets and their quality possible. Otherwise they are determined based on expert knowledge or a combination of both methods. To prevent further expansion of scope and the complexity of existing problem expert knowledge was applied to determine the attribute weights. Furthermore, it is possible to have more than a single weight vector. This approach is useful, if there are various object types or parts, which have different prioritization for their attributes. [START_REF] Zhang | State-dependent weights in multicriteria value functions[END_REF] To identify the objects with most similar product assembly information for a new object the classification algorithm k-nearest neighbour (kNN) [START_REF] Dhanabal | Review of various k-Nearest Neighbor Query Processing Techniques[END_REF] with Euclidean distance as evaluation function is used. From the identified objects a list is generated and the most related one can be manually chosen, which passes its assembly process data to new object. To assure the reliability of the presented method and prevent over fitting a cross validation [START_REF] Kohavi | A study of cross-validation and bootstrap for accuracy estimation and model selection[END_REF] is used.

Fig. 3. -PAI attributes example screwing connection

The implementation of the presented approach is challenging due to high requirement for interconnection and the overall quality of the existing data in different source system. In particular the pure number of realized and existing assembly connections and thus necessary instances of an product assembly information as well as the quality of the data regarding their attributes are important.

Momentarily the fulfilment of these high requirements have to be verified. In particular the quality of the linkage of product data with the corresponding assembly processes poses a challenge. Methods to improve the for this concept important quality will be evaluated. Is this task solved the selection of the properties and attributes for the data mining analysis also has to be determined based on production data to ensure the reliability of generated results. In this scope a special focus is on the characteristics of the parts and of the connection itself. In conformity with the presented objectives and concept a utilization of the methodology is described as follows.

Suggesting assembly connections and enrichment of CAD data: The designer creates a new module with already known and new assembly connections in the CAD system. He designs assembly connections and complements these connection properties in the context of the new module. Via the automated Data Mining process, he is provided with various information about the assembly connections. Moreover, for each assembly connection a list of alternative or ever realized connections can be created. Depending on the product properties the five most similar product assembly information are made available to the designer as a prepared proposal list, which is generated through cluster analysis of existing product data. These information can be used directly and enhance the CAD model in order to use it later or in an extended context of the product. If the analysis is dispensed with the filtering of associated connections with the product assembly information, the designer can also be provided with other not associated connections as alternatives.

Estimation of assembly process and information:

The production planner drafts an initial assembly process for a new assembly at an early stage of product development. Analogous to the use case of the designer, for known assembly connections that are implemented in the new product as well as in the old product data, the right product assembly information and thus the assembly processes are found. For new unknown connections the most similar product assembly information and related assembly processes from the database are determined and duplicated. Each of the founded product assembly information represents a single connection and the linked process represents precisely the assembly work content for this connection. The sum of the individual connections for the new product is its first assembly process. Thereby an initial draft of an assembly process of the new module can be generated. The founded individual connections, the individual process, as well as the overall process can be used in different ways to assist the designer and the production planner. The planner and designer also get a first estimation for the expected assembly time and cost in the automated process. In addition, the production planner can increase the quality of the process by manual intervention. On the one hand he adapts the product assembly information, which are created by the designer, before the Data Mining analysis. On the other hand he can complete the product assembly information in the attributes with practical knowledge. Thus he has an impact on the input of the Data Mining analysis and increases the quality of the result thereby. Furthermore, the designer has a first draft for the assembly process at one's disposal and a first estimated assembly time in the current CAD system. By a company-specific factor, the designer receives also information about the cost of the connection in the assembly. By verifying this information, the designer can evaluate and compare the alternatives for different connections.

CONCLUSIONS AND OUTLOOK

Through utilization of Data Mining tools the efficient design of assembly connection, the quality of planning results and planning processes can be increased, while simultaneously time and cost reduction can be realized. In this regard, the presented approach contributes an important added value to production design and planning through usage of knowledge in the existing systems. Thus reduction of planning time, increasing availability of information in product design as well as making the cooperation between the designer and product planning teams easier are the consequences. The feasibility of this concept with productive data is in evaluation. New approaches with clustered data to improve data quality are in an assessment. However, to produce reliable outcomes the product data have to fulfil high requirements in regard to connection elements. Concurrently the necessary data model and some tool sets are provided to make the data integration easier. In the future further development of tool sets and methods could help to reduce the high initial effort for adjustment of the data even more. Besides the evaluation of the results based on product data it is important to investigate the behaviour and results of the methodology for new and innovative assembly technologies. Furthermore, for analysing more complex data sets as well as obtaining better results, it is important to develop and refine the concept and to apply further Data Mining methods.

Fig. 1 .

 1 Fig. 1. -Design optimization with additional time data.

Fig. 2 .

 2 Fig. 2. -Data model overview.

ACKNOWLEDGMENTS

The research project "Prospective Determination of Assembly Work Content in Digital Manufacturing (ProMondi)" is supported by the German Federal Ministry of Education and Research (BMBF) within the Framework Concept "Research for Tomorrow's Production" (funding number 02PJ1110) and managed by the Project Management Agency Karlsruhe (PTKA). The authors are responsible for the contents of this publication.


Vokhmintsev Alexander

Melnikov Andrey

The Knowledge On the Basis of Fact Analysis in Business Intelligence

Keywords: Fact analysis, semantic network, knowledge base, full-text databases, ontologies, text mining, data processing, applied linguistics, fact extract, factual data model, syntactic-semantic tree of dependencies

This article discusses the problem of searching and analyzing scientific and technical information gathered from open sources in the field of business intelligence. Subject area is represented through ontological model extended by fuzzy links between objects. Using this ontology-based approach, we have created "Cyber-analytic", information analysis system which is capable of extracting facts from natural-language texts in Russian and English, and representing them as object relationships. We use i2 Analyst's Notebook. as a visualization tool.

INTRODUCTION

Modern information technology is characterized by rapid growth of data volumes of different kinds (text documents, relational databases, multimedia and biometric data, etc.). Major part of the data is produced in form of natural language texts (according to Gartner, more than 96% of data falls in this category.) This way of representing information is most natural for the human being because we use natural language constructs in our thinking processes. At the same time, this type of information requires complex models and algorithms which help to build formal representation of text document through linguistic analysis.

As of today, there are successful systems for linguistic analysis based on morphological text analysis (including those with fuzzy search algorithms), thematic analysis, building of semantic portrait of text document, and intellectual ontology based systems for specialized subject fields. As a result of morphologic and thematic analysis, usually a bundle of thousands of text documents is formed, where documents are sorted by relevance. This amount of documents is very difficult to analyze, that's why with the development of Internet (the biggest depository of text documents) new ontology-based methods of semantic analysis of text documents started to appear. The term "ontology" was used in several AI research communities, firstly in the field of knowledge engineering, natural language processing, and later in knowledge representation (Jos de Bruijn, Fensel D., Staab S., Studer R.). Later on, ontologies started to be regarded as key element in Semantic Web project. The main drawback of those methods is that they can be used in practice only for information systems working with narrow subject fields (for example: industry, metallurgy, mechanical engineering, power engineering) where it's possible to precisely describe technology and business processes of a company. All attempts to use these methods for more general cases (for arbitrary subject fields) were unsuccessful.

To solve this problem in general case, it is necessary to use methods based on deep syntax-semantic text analysis, which fall into three main groups:

 syntactic methods: analyzing syntactic characteristics and lexical composition of texts;  statistical methods: establishing of semantic links on the basis of extracted statistical relations;  semantic methods: those methods works through exploring deep semantic connections in a sentence, a text document and beyond (for example: knowledge base, thesaurus, ontology, explanatory dictionary, etc.).

Research on deep semantic analysis of texts has been carried out for quite a long time, including works of N. Chomsky (transformational grammar, universal grammar), I.A. Mel'čuk ("meaning-text" model), G. Scragg ("Semantic nets as memory models"), R. Schenk ("Processing of conceptual information"), C. Fillmore ("Frame semantics and the nature of language", "The Case for Case") [START_REF] Mel | Actants in Semantics and Syntax. I[END_REF][START_REF] Chomsky | Rules and Representations[END_REF]. In these methods, semantic analysis uses knowledge bases which contain information about subject area.

In this article we'll discuss following points:

 Describing the knowledge model to store data on monitored objects of scientific and technical information;  Developing a method for factual analysis of text documents for knowledge bases;  Applying the method of factual analysis in "Cyber-analytic" information analysis system.

ONTOLOGY BASED MODEL OF KNOWLEDGE BASE

Considerable proportion of scientific and technical information in modern world is open, especially during the stages of idea formulation, discussion and approbation.

Counter-espionage services and industry use this open information for the purposes of industrial design (e.g. pre-production models, classification of documentation) or promotion of science intensive products on the market. To solve the problem, an expert would integrate the knowledge, analyzing heterogeneous information produced by other scientists and engineers in order to get some knowledge on the object or technology in question. In this case, electronic Internet resources (scientific articles, conference proceedings, industrial and business news, professional resources), design documentation, offline publications in scientific libraries and social networks (online conferences, forums, blogs) are the main source of information.

Fulltext databaseis a set of cross-referenced documents, which can be most adequately represented as a semantic network. To store detailed information about subject area, the information needs to be supplemented by set of ontologies and metadescriptions of knowledge contained in text documents (Berners-Lee T., Hendler J., Lassila O.) [START_REF] Manning | Foundations of Statistical Natural Language Processing[END_REF]. Thus, we can introduce a definition of ontology for the purpose of scientific and technical monitoring: T -timeline of the object (change of object attributes over time). Proposed knowledge model has advantages over traditional ontologies, as well as over semantic networks, since the objects are viewed in context of source text document (paragraph, sentence, etc.) and chronological timeline. This approach permits to separate morphologically equal lexemes using semantic information about their attributes, contexts and object timelines. For example, persons "Angela Merkel politician" and "Angela Merkel florist" will be separate in semantic search results.

In the process of monitoring full-text document collections, analyst tries to find in texts some regular patterns, events, persons (organizations), product names (technologies), and their relationships. In modern applied linguistics these constructions are called facts [START_REF] Feldman | The Text Mining Handbook[END_REF]. The figure demonstrates graphic representation of a fact: relationship between a person and an organization in the context of employment.

FACTUAL ANALYSIS OF TEXTS

Knowledge bases can be built by subject area experts, but also automatically using Text Mining algorithms that extract data on objects, their attributes and connections using formal rules. Among tools for semantic analysis we could note Convera Re-trievalWare and Russian Context Optimizer (for documents in Russian language) [START_REF] Bayer | valuation of an ntology-based Knowledge-Management-System. A Case Study of Convera RetrievalWare 8[END_REF].

In this work we will discuss the factual analysis method of natural language texts, which allows to extract information on monitored objects using predefined semantic inference rules. Let's introduce basic definitions.

 , n i a i , 1 ,  -attributes of subject area concept, so that     n i i a 1 .
Examples of target objects: artificial intelligence, . N Ruhrgas, urgen M ller, one thousand years ago, DE0008469008, US78378X1072, +49 (0) 172 9587 163, $3000, 98%.

Target objects (TO) can be subdivided into two classes: significant TO and insignificant TO. Insignificant TO include all auxiliary sentence elements not having any meaning by themselves (service parts of speechunions, prepositions and punctuation). Significant target objects, in their turn, fall into three categories:

Definition 3 Semantic network

Nodes of semantic network are the TO, mentioned in the text, links are all the different types of syntactic and semantic relations between the objects. The simplest semantic network is a result of syntactic analysis and additional semantic transformations of the syntactic dependency tree in a given sentence. Let's call tuple



Connections in semantic network have the following set of attributes:

 ) , /( ) , ( ) (      x x x x H R   
-degree of contiguity of nodes in the semantic network (grade of membership); Semantic network of a sentence is an example of fact in its simple form. More complex facts could be defined through anaphoric or other references in the paragraph, text block, text document or collection of text documents. Factual analysis can be broken down into following main stages [START_REF] Vokhmintsev | Integration of proffessional knowledge bases with the help of factual analysis and ontological models[END_REF]:

1. Pre-syntactical analysis  morphological text analysis;  processing of word forms not present in the dictionary;  identification of stop words;  preliminary analysis of typical structures in text document.

The result of 1st stage of processing is a set of sentences, where each sentence contains ordered list of words with variants of homonymous lexemes.

Syntactical analysis

 extraction of standard sentence constructions using the morphology data, building of word-combinations;  identification of syntactic and semantic constructions in the text;  construction of syntactic and semantic dependency tree.

After the 2nd stage, the set of syntactic and semantic dependency trees is formed. The most probable parsing variant is then chosen using heuristic algorithms.

Post-syntactical analysis

Analysis of word forms not included in final variant of syntactic and semantic dependency tree.

Semantic analysis

 extraction of target objects from the text;  building the logical scheme of the situation;  classification of semantic networks;  context analysis;  chronological analysis, elimination of collisions.

The result of 4th stage of processing is a set of target objects with semantic connections. To extract target objects, it is necessary to build the logical scheme of the situation. Resulting set is then classified into categories.

Rule of extraction of target objects (Person: Full Name): Factual analysis of the text can find descriptions of situations corresponding to certain templates, for example invention of address bus or stock purchase. Fact search is performed within semantic network of text document. Logical scheme of the situation identifies class of possible situations and contains slots that unambiguously separates it from other situations. Semantic analysis module fills the slots with values, some slots can be left empty. Further, semantic module relates the set of sentence semantic networks of text document with corresponding template than defines a fact, using modified decision tree algorithm С4.5. according to the situation templates in the knowledge base. Factual analysis also employs statistic methods to calculate frequency/weight of target object or its connections in the document. Statistical methods are based on the calculation of TF*IDF.

«CYBER-ANALYTIC» -INFORMATION ANALYSIS SYSTEM

Applied software lab of Chelyabinsk State University has been developing text mining analytical systems since 1998. "Cyber-analytic" has indexed more than 2400 Rus-sian and English document sources, including major media such as Vesti, New York Times, BBC, Interfax, etc. Fact search in "Cyber-analytic" information system uses ROLAP approach because it consistently shows good performance in software solutions for financial planning, data warehousing, and Business Intelligence. OLAP cube is created from table join using star scheme, with fact table at the center of the star. Multiple tables with different indicators are joined to fact table. The system has large number of predefined analytical queries, corresponding to subject field ontology.

For the present problemmonitoring of scientific and technical informationthe following indicator tables have been created: Analytical queries are created with the help of query creation tool, and it's important to note the the analyst can use natural language when formulating the context dependencies. Query results are displayed to the analyst in the form of analytical diagrams. "Cyber-analytic" employs i2 Analyst's Notebook software as its visualization tool.


There are three types of diagrams:

1. Link Analysis charts -shows connections between persons, bank accounts, organizations, phone numbers, property and other things. We can then use the filtration of the score relation. But the frequency factor should be considered carefully, as the only fact may appear the most important in the analytical research. The figures show the request results in the form of analytical scheme in the system of visualization i2 Analyst's Notebook. If the analyst click on the link between the objects, he receives a list of documents with the abstract where the facts about the pair of objects are revealed. In addition it is possible to get information about the attributes of the objects. After studying the structure of relationships between semantic objects analytic turns to natural-language texts containing the relevant information.

CONCLUSIONS

In this article we discussed application of ontology knowledge models to the task of monitoring objects in the context of scientific, technical, and business ingelligence. We proposed a method of factual analysis of full-text databases that allows to automatically extract situation descriptions that correspond to pre-set templates. Resulting situation descriptions are used by experts to form knowledge base in the subject field. Ontology knowledge model and method of factual analysis are implemented in "Cyber-analytic" information analysis system.

  semantic network, l inking the object to other objects;  properies O -object characteristics;  p A -manipulations with the object;  a A -actions of the object;  С -contexts of the object; 

Fig. 1 .

 1 Fig. 1. -Graphic representation of a fact

  Every target object has the following set of attributes: i A -Target object identifier is represented by a normalized string or known object identifier (person ID or organization ID);  class A -target object's category. It is also possible to define custom categories; (part of speech, genger, number, case, person, etc.); of TO include its distinctive features, for example: first and last names for a person;  ref A -set of links to all text sentences that mention the TO;  c A -communicative characteristics -set of attributes, determining communica- tive position of the TO in the sentence: part of the sentence and type of syntactic construction (clause).

  the semantic and syntactic relation between nodes: ablative, agent, addressee, argument, derivative, destinative, causative, characteristic, membership, etc.; role e-semantic role defined for connections between predicate and argument, usually taken from the list of government models, for example subject, object, instrument; case e -semantic case and connector (preposition, union) between nodes in dependency tree; sentences in text document.

  macro: strict_full_name ( (name_feminine (middlename_feminine)? (nastname_feminine):morph_info ) | (name_masculine (middlename_masculine)? (mast-name_masculine):morph_info ) | ((lastname_feminine):morph_info name_feminine (niddle-name_feminine)?) | ((nastname_masculine):morph_info name_masculine middle-name_masculine)? ) | ((name_feminine):morph_info middlename_feminine) | ((name_masculine):morph_info middlename_masculine ) ):whole_strict_full_name rule: strictfullnamerule strict_full_name --> :whole_strict_full_name.token = { semantictype = "fullname:fullname", type = "word" }, :whole_strict_full_name.morph = { :morph_info.morph }, :whole_strict_full_name.rule = { rule = "strictfullnamerule" }

Fig. 2 .

 2 Fig. 2. -Link Analysis charts

Fig. 3 .

 3 Fig. 3. -Sequence of Events charts 3. Transaction Pattern Analysis chartsdiagram of this type help to recognize and analyze recurrent patterns of events, for example electronic mail messages, sms, phone.

1 .

 1 Named objectsthis class includes following semantic types: persons, organizations, geographic objects, technology and product names, and other proper nouns. 2. Unnamed target objects -this class includes full words of following parts of speech: common names, adjectives, auxiliary verbs, animated and unanimated objects, object attributes, events. 3. Special target objectsentities encountered in some special constructions in text, consisting of alpha-numeric characters: dates, adverbial modifiers of time, money amounts, identification data of people and organizations, etc.

	Definition 2 Target object attributes
	t A	arg	et		{	i A	,	class A	,	morph , A	syntactic A	,	, semantic A	,	,	}


Heike Wilson
email: hwilson@dualis-it.de

Reik Zettl

Simulation and Optimization based Flexible Job Scheduling of Powder Coating Lines

Keywords: Material flow simulation, Advanced planning and scheduling, optimization, powder coating lines, ERP, PLC, shop-floor control, order sequencing, production order mix, delivery dates, multi-criteria optimization, 3D simulation, 1

The Paper will present a new approach to use simulation methods combined with intelligent optimization algorithms in an operative scheduling and monitoring application for powder coating lines. Powder Coating lines are built usually as a closed loop "power and free" chain system that transports the products on carriers from a starting point through the different production stages. Due to the closed loop, efficiency and the overall output of the system is highly dependent on the sequence of the production orders entering the line. Inefficient sequences can cause deadlocks, significant decrease of the production output or even scrap production. The presented application architecture is based on a 3D simulation platform working together with a closed loop heuristic sequence scheduling algorithm. The paper will also introduce the system architecture design with full integration to an enterprise IT structure comprising ERP, real time PLC communication and a Warehouse Management System.

INTRODUCTION

Globalisation and the associated pressure on costs has increased considerably during the last decades and most production companies, especially small and medium size enterprises "SMEs", are forced to continually adapt, most often through better production flexibility and efficiency. Surface treatment and coating production usually supplies products to internal finishing and assembly lines or to external customers, but always "just-in-time" or "just-in-sequence" where the throughput-time is as short as possible. Quite often production order information arrives at very short notice to the coating process leaving little time to make a decision, let alone an optimal one, about the order sequence. Ideally the decision must be based on various parameters such as status of current production orders, requested delivery dates, equipment and buffer utilization and order properties like sizes and colours and so on. This complex information increases the pressure on optimized planning combined with a high product quality and processes stability. Most companies still rely on manual scheduling and have to learn from painful experiences of lost earnings and efficiency before thinking more about lean manufacturing processes, integrated with flexible and affordable IT-Systems. Manually based solutions limit the information flow between the ERP level and shop floor production management, placing an increased burden on the coordination between departments.

In contrast, large manufacturing enterprises have been utilising technologies based on industrial simulation toolkits and mathematical based optimisation algorithms to support shop floor production planning already for some time. In the presented solution based on successful implemented project examples, available simulation technologies were combined with automatic scheduling in one decision support system that delivers required information to the planning department very fast and always based on the current production system status. The available 3D model of the powder coating line was enriched with additional operation logics, linked to the PLC and the ERP-system, and combined with fast heuristic scheduling algorithms in one integrated IT platform. The results of the scheduling is used to constantly control and optimize the material flow inside the powder coating line by delivering optimal decisions for each production stage.

The advantage of such a solution where 3D simulation models can be reused for supporting tasks like scheduling and line control is high for an SME. However few industrial case studies exist where Virtual Factory models initially used for layout proposals or a simulation study have been re-used for production scheduling, monitoring and control.

PROJECT OVERVIEW

Project Partners

Rippert Anlagentechnik GmbH & Co.KG is the system supplier of both implemented powder coating systems. The are located in Herzebrock-Clarholz, where the mid-size company successfully holds its own in the market with three divisions covering coating plants, filter systems and industrial fans. This system supplier has been developing, producing and installing state-of-the-art, energy-saving plants for industrial customers all over the world for the last 45 years. As a long term application user of the 3D Simulation toolkit (powered by the Visual Components Oy) Rippert was also very interested in the idea to enlarge their own plant visualization system with simulation and optimization based technologies. The main idea from their side was to offer the customer a new integrated solution providing four additional functionalities besides the visualization -3D simulation, line monitoring and control and above all intelligent optimization based order scheduling.

The second project partner the mid-size company Louis Schierholz GmbH provided the Power and Free closed loop system inside the powder coating process. Schierholz Power & Free offers optimum flexibility by using a revolving chain on a closed loop, with unit load conveyors shifting loads on a running gear connected to a rail. The running gear and chain are linked via an interlocking catch system. Running gears can change chains at transfer points, and material flows can be separated or combined. Stoppers keep the running gears separate from the conveying chain, and help create storage areas, feeding, removal and operation points. One of the main tasks in the project was to connect the 3D simulation model with the Schierholz PLC in order to get the online information for the gears in the operating system to control the process flow for keeping optimal production sequencing.

DUALIS GmbH IT Solution the third implementation partner was responsible for the software development and integration of the IT-Platform at the customer's plants. The company is located in Dresden, Saxony, and has been providing simulation consultancy and software solutions as well as optimization based scheduling applications for over 20 years now. Founded in 1990 by Professor Wilfried Krug, DUALIS now has over 200 worldwide customers who have been able to improve and optimise their production processes with tools based on specialised mathematical algorithms for optimisation. DUALIS mathematicians and developers work together to improve techniques for solving real world optimisation and scheduling problems in the Automotive, Packaging, Automation Assembly and Logistics industries. The company's latest software development is an optimisation based short term scheduling architecture for small and medium sized companies in the production planning area. The architecture has a planner and constraint solver algorithm optimising for several and often conflicting optimisation goals based on a production system with finite resources and capacity. Expanding their applications with shoop-floor and PLC connectivity is a logical step to offer complete solutions based on simulation and optimization and to meet actual customer requirements.

Application description

In today's manufacturing environment simulation techniques are used to reduce risk mainly in the planning phase for "green field" production plants or the reorganisation of an existing facility. Both 2D and 3D industrial software packages are available for these types of tasks and the derived models are often very detailed and rich in process information. In many cases logistics functions and physical detail is so close to the finally implemented system an opportunity exists to reuse the models to support the end-user's daily processes, such as production scheduling.

Driven by the challenge to get the highest possible efficiency from their powder coating systems, Rippert uses 3D Simulation to optimize the Power and Free system, buffer areas and system parameters during layout design in an early sales phase. With pre-defined product mixes, simulation runs are used to optimize the utilization of the processes and show the client the virtual system with product data as realistically as possible in a "virtual plant". After the planning phase is finished and product parameters like output per shift are agreed and fixed, expectations for real line operation need to be met. The Rippert application used existing simulation models for operative short term scheduling and line monitoring. An approach that can be of particular interest to other line builders and modular equipment suppliers who are already working with complete machine model libraries and working 3D simulation layout models for presales. These types of companies, would be able to extend the use of the presales models and provide a scheduling tool as an option for every turn-key production system delivered: to help their customers get the best out of the production system. This ap-plies to most operators that need to schedule, monitor and optimize daily production and react when operational parameters change. In particular, manual changes to production sequencing in a closed loop chain driven system is very hard to successfully accomplish. Sequence scheduling before production start is very important. The Rippert application includes manual scheduling as well as heuristic optimization which can be adapted and customized if needed. The operator is able to define the product route and process times either manually or by importing the actual order pool from the MES (Manufacturing Execution System) and apply only changes. Based on the actual system load the generated sequences can be simulated and evaluated by the operator using defined KPIs. The optimal schedule is created using the integrated optimization engine with different optimization goals, production constraints and parameter settings. Once the sequence is determined it can be uploaded to the M.E.S to load new production order information to the real system. But uploading the optimal sequence is only one side. The many decisions points in the system need ot also also controlled in order to apply the optimal schedule to the system. Especially for the closed loop system minimal changes in the product sequence can cause trouble setup requests at the coating cabins or even deadlocks at critical for example oven processes or buffer areas. Therefor the final integration also links to the sensors and PLC controls in order to manage the decision at switches, feeding, operation and/or removel points as an essential task to also fulfil the optimal schedule.

Integration concept

Currently SME companies are managing their production facilities using different IT applications. In most cases the applications have grown organically based on specific user needs. As a result, many of the IT sub-systems within one company have evolved with duplicate functionality. The end result is a confusing IT landscape where it is unclear which sub-system can and should deliver the required services, or where new functionality should be developed.

Missing from the SME IT portfolio is an integrating architecture where the required functionality is available through one common interface. Efforts have been focused on ERP (Enterprise Resource Planning) systems but there is little connection to the shop floor, especially in the areas of planning and optimisation. In the last couple of years a clear need has emerged for the research and development of improved ERP support tools for production.

These applications are commonly referred to in larger enterprises as APS (Advanced Planning and Scheduling) tools. To support an integrated solution for the SME with full Product Life Cycle Management the APS application must interface on the ERP side to a master data and to the shop-floor PLC on the other side.

The project is based on the most common vertical integration within the IT infrastructure between ERP, APS and MES/PLC applications as depicted in the following diagram (e.g., Fig. 1) The main administration and order data is stored in the ERP-system. The pilot project ERP-systems were using common databases such as MS SQL and Oracle. In order to stay platform neutral the application connects this Administration level with the production MES level using stored procedure links implemented in C#. The goal was to implement a generic interface in order to reuse the connection strings in further projects with different ERP-systems, databases and PLC-applications.. More implementation work was required at the APS-level. The 3D simulation models used for system design and optimization during pre-sales and engineering had to be supplemented with PLC information representing the real shop-floor system. To monitor using a 3D model requires a unique and realistic representation of each Power and Free section and production process stage. Every section of the Power and Free system is modelled with start and end sensors to register the information of the entering and leaving gears. In order to visualize the correct gears and information about the transported products in each sector the sensors need to be modelled with real-time connectivity to the PLC/OPC-application data. In each section the actual number of possible gear buffers are implemented. Each buffer place has a unique address managed by the PLC-server. With the provided address the APS-application can check if the sections are loaded and carry out the real time optimization process based on this information. For each optimization run the actual gear load in each system will be read from the PLC using this adress. Product information like type, colour and other important specifications are available from the PLC data as an input to the optimization. Based on this information the scheduling heuristics creates now new sequences in different areas based on the optimization goals set. The project experience shows that the setup time optimization at the powder cabins and promise to deliver at the final assembly are most important. The main goal is to schedule long colour batches with minimized cleaning and setup times between different colours. Lowering the down times at the colour cabins increases the system efficiency and overall product output significantly. Besides setup optimization in more complex powder coating lines the decision points at intersections and crossings become more important. The same applies to product mixes with repeating product routes. Since the decision of which gear will be released for instance from buffer areas will have an impact later on at following productions stages. Therefore the actual status must be updated almost online from the PLC, adjustable to the user requirements.

CONCLUSIONS

The benefits for the planner in comparison to available short term planning based options, that do not use simulation and optimization is the ability to quickly pre-test a calculated optimal schedule, and allow visual feedback to the planner about the actual system status combined with planning results. Further more using the PLC linkage the schedule will be online updates and adapted to the actual situation at any time. System deadlock and unnecessary colour setups are minimized. Both user plants increased the number of gears going through powder coating per shift by about 15%. The next challenge will be to not to look only at the coating line as single optimum but also include all pre-successors and successor stages into the optimization model in order to achieve a total optimum for the plant. General benefits from using simulation and optimization as well as the operative scheduling benefit can be summarised with:  Modelling of complex systems and networks for better understanding  Fast and flexible adaptation to changing production system environment  optimized production schedules  Test "what-if" scenarios on the virtual production system without any real term consequences such as production loss and interruptions.  Fast scenario testing and future prediction capability for planning purposes  Better understanding of the production system  Cost effective validation of new ideas or strategies  Faster analyses and results  optimized production schedules with cost minimization and more overall system efficiency 4 REFERENCES

Fig. 1 .

 1 Fig. 1. -Vertical Integration of Administration and Production systems

Fig. 2 .

 2 Fig. 2. -Operating 3D model of an Rippert powder coating system


Andreas Barth
email: andreas.barth@3ds.com

Andreas Barth Vp

3D Experiences -Dassault Systèmes 3DS Strategy to Support New Processes in Product Development and Early Customer Involvement

Keywords: 3DExperience, CATIA, Innovation, DMU, Smart Product 1

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

INTRODUCTION

Innovation is driven by change and the consumer markets do change rapidly these days. Mobility requirements for instance do have strong impacts on the Tele-Communication Industry (mobile devices such as smartphones, tablets …) and on the Transportation & Mobility Industry (Electro mobility, personal mobility, sustainability …). It's the first time in industrial history that innovation is more driven by end consumer needs rather than by engineering and manufacturing companies.

WHY IS CHANGE NECESSARY?

It is a complex challenge to move from traditional engineering to Smart Product development. Forward-thinking executives are, quite rightly, demanding more and better consumer insight and smarter research to measure impacts of potential new innovations. Companies can gain an understanding of their customers which is better, faster, and less expensive by doing four things called the "digital research revolution":

1. Leverage the digital society power to rapidly create and deliver detailed information about what would be products customer acceptance information. 2. Recognize the limitations of the measurement systems based on projected past or isolated focus groups.

Seek to understand what customers value the most and how technologies and inno-

vation can deliver and enhance the product value. 4. Link investigations into consumer insights based on virtual product candidates that are sorting value very close to their customer relationships management systems and create criteria such as "Cool Feature", "Must Have", etc.

Leverage the power of the Digital Society

The Internet is fast. It enables any type of digital exchange and can leverage data in many forms plus has the ability to create many more iterations with a turnaround in a few days, rather than weeks required for traditional methods. Marketing strategy segmentations for innovation that used to take months can be completed in weeks. Working digitally is also less expensive than prototyping/ face-to-face studies and can be conducted with dramatically larger sample sizes. Finally, customers' online comments, search behavior, and other revelations offer a prove of data.

Decrease reliance on traditional prototypes and focus groups

Focus groups were once the default qualitative research approach. Companies gathered small numbers of consumers in a facility around real prototypes for some hours, promised them a small payment or free products, and asked them to give simple written or oral answers to questions that may or may not have provided real insight. Despite the emergence of better alternatives, little has changed yet. Full usage of Virtual Product candidates now enables leading marketers to create deep immersion experiences with a large number of users organized through communities to generate consumer insights and new products; consider values and positioning; and redefine a product's competitive set. These ideas can then be tested quantitatively, either through further research or a market pilot.

Understand how successful products are created

Companies have long focused on what and why people buy. Research data from consulting companies like Oliver Wyman show that this is not sufficient.

They clearly show that only few high-quality products are magnetic 1 , defining "magnetic" by a simple equation: M = F×E. Magnetic equals best functionality times most powerful emotional connection with customers. Very good functionality is obviously not enough anymore.

Connect what you know about consumer value

Why do consumers disproportionately demand one product over a seemingly similar one, often by a factor of four or five to one? Functionally and technically, products might be close; emotionally, they can be worlds apart. Why do seemingly similar products produce radically different demand curves? Demand creators, people who design products that truly excite consumers, are obsessed with understanding customer values, and connecting the dots from multiple value chains to fix it. They don't assume that buying = wanting. They use the value map to recognize the huge gaps between what people buy and what they really value including emotionallyand use those value map as a springboard to see differently. Demand creators crack the mystery of the demand equation by doing a radically better job answering a small set of critical value and differentiation questions very well.

THE CONCEPT OF 3DEXPERIENCES BY DASSAULT SYSTÈMES

How can a Software tool vendor support demand creators? 3DS has initialized a large change to apply the power of the Digital Society to help product creators with the new challenges described above: Introduce the ability to create Smart Products from an unified digital representation that are all interacting together to create a "Virtual" Smart Product.

To reach customers but also to ensure that fast development cycles based on value of a product that can actually be produced can be achieved digitally, a "Virtual" Smart Product needs to be digitally accurate. This product accuracy is not sufficient to help creators if it is not also possible to benefit from similar accuracy in the digital modeling of the environment in which the products will be used.

And of course measuring value and making product creators able to deliver the magnetic products described above means that ability to interface with large communities and finally partners including suppliers, channels and consumers are requesting interacting socially in fast and efficient digital loops.

3DS has started to create a Product Creator Digital Platform that has the ambition to complete the digital landscape compared to other platform technologies  Facebook as a social platform Google as a search platform  Wikipedia as a knowledge platform App stores as a services and applications platform The target is to provide the same accuracy that was obtained on geometry to the other engineering domains. The target is not to provide game platforms but to enable the magnetic product creation to be done socially based on the real physics and manufacturability of the products -this can be seen as a natural extension to the Product Lifecycle Management market (PLM).

The representation of this strategy is indicated by a user interface to access the software and data platform in the form of a compass as a synonym for a highly integrated application environment and a platform concept.

USER EXPERIENCES BY INDUSTRY

The 3DS new 3DExperience platform is to be delivered for 12 industriesthat produce Smart Products including the more traditional customers of the company such as Automotive, Aerospace and Industrial Equipment to new customers such as high volume Consumer Packaged Goods, Retail, Energy, Process and Utilities, Financial and Business Services, Life Science and more.

PLM Innovation by Engineered Business Experience

Overall the changes, whether it is the market, the consumer buying behavior, new products, changed mobility etc. have a significant impact on the way engineering will work in the future. The purpose of this experience is to understand how the customers are expecting the next generation of the mobility services by providing some innovative ways to collect their needs and identify the market trends, to enable crowd-sourcing and cocreation around new concepts and social innovative design. Powerful 3D design tools to boost the industrial innovation process and efficient tools to perform virtual car clinics and showroom, with augmented reality and immersive reality, will be introduced. A virtual in-car feeling by enabling new in-car experience, including driving experience will lead to new design and engineering front loading experience, thus reducing the time to market and reducing physical prototypes.

Lean, Green and Compliant.

The purpose of this experience is to improve vehicle energy efficiency upfront with light weight and green propulsion and to explore new ways of progress by optimizing the energy balance and the weight. Providing an end-to-end solution for EV and HEV propulsion concepts development accompany companies in their will to be more environmentally responsible. An integrated platform for vehicle validation and certification to define, manage and monitor the validation and verification process (physical and virtual test) insures requirements validation. The compliance towards global regulations and certifications (material compliance, FMVSS, CAVA, passive safety, etc.) help to optimize the vehicle performance globally and by providing a multi-physics simulation platform to evaluate and optimize all the performance of the vehicle, increased product quality and satisfying sustainability results can be harvested.

Smart, Safe and Connected.

The market today is challenged by a re-invention of the mobility experience as 80% of vehicle innovations are coming from embedded systems and development moves from vehicle attributes to vehicle experience. A huge complexity in the number of ECUs, lines of code of software and an increasing number of functional requirements makes car design error prone, resulting in 20 to 40% of vehicle development cost spent in testing and diagnostics. The market demands to improve quality and safety and decreasing the number of warranty cost and cars recalls. To demonstrate functional safety against class actions lawsuits and to standardize on industry initiatives such as Software re-use (AUTOSAR), Strengthen safety (ISO26262) and early validation are mandatory to support next generation car developments. The concept of Functional Mock up that integrates mechanical, electronics, software and simulation, is key to design and simulate the car of the Future: smarter, safer and always connected.

Modular, Glocal 2 and Secure.

This experience allows defining the technical requirements from a marketing analysis and ideation process done on unstructured data, to define the vehicle portfolio and monitor the program: project dashboards, program 360° and quality plans (incl. suppliers). Platforms and modules, interfaces as well as the vehicle architecture (volumes, technological choices, etc.) are managed along the defined configurations. The management of the EBOM is based on a modular approach and support the Digital Mock-up review processes (Design, Manufacturing and Simulation) in a distributed environment (Suppliers, R&D centers,). The MBOM manages the assembly processes per manufacturing plant and the supply chain, from engineering to after sales, including sourcing, RFQ/Supplier choice process, and the contract and cost management, etc. are integrated as well.

Target Zero Defect.

To ensure a zero defect process End-to-End on all the domains, extend the zero geometry defect to the End-to-End, and taking full benefit of new system engineering and collaboration environments is the purpose of this experience.

Capitalizing and reusing knowledge globally for design, manufacturing and simulation will promote innovative tools and methodologies in Architecture and Conceptual phases of the processes. Augmented simulation contribution and key differentiators in all steps of the processes will improve productivity and efficiency to reduce cycles by providing Best-of-Class solutions.

CONCLUSIONS

With the 3DEXPERIENCE platform companies create "social enterprises" that involve their customers in the innovation process. With its online architecture the 3DEXPERIENCE environment enables businesses to test and evaluateanywhere in the development lifecycle of a product or servicethe eventual experience they will deliver to their customers.

1Fig. 1 .

 1 Fig. 1. -3DExperience Platform compared to other platform technologies

Fig. 2 .Fig. 3 .

 23 Fig. 2. -Dassault Systèmes supports 12 Industries

Fig. 4 .Fig. 5 . 5 . 1 . 1

 45511 Fig. 4. -PLM Innovation


Björn Schuster
email: schuster@nupis.de

Dipl.-Ing Björn Schuster

As-Is Analysis and Efficient 3D Layout Planning during the Conversion of Old and Design of New Production Facilities by Means of 3D-CAD

Keywords: Digital factory, Factory Design, 3D layout planning 1

INTRODUCTION

The quality of factory planning today is an important factor to ensure the competitive position of factories. Global competition calls for the best possible planning and a permanent optimisation of the production processes, which is why the constant improvement of models, methods and tools for factory planning and operation is very important. The challenge facing many factory planners in connection with this development is to plan and implement the conversion of old and design of new production facilities as efficiently as possible.

DIGITAL FACTORY PLANNING USING 3D-CAD SOFTWARE

The majority of CAD data that is relevant for a factory today is available in 2D drawings and can only be transferred to a 3D format in stages and for specific projects on account of the effort involved and the generally existing departure from reality. There are a large number of software tools that allow virtual reality to be used to visualise the manufacturing planning of a factory. Virtual reality has become established in product development under the catchword CAD (Computer Aided Drafting) and is used in factory planning under the concept of a 'digital factory'. 'Digital factory' therefore means a virtual two-or three-dimensional representation of the factory to carry out real planning and a test-driven simulation, in particular to visualise a material flow analysis.

The use of 3D-CAD software accelerates the planning process since the planner can develop and communicate an efficient factory layout using a digital model. The subsequent simulation of a factory is understood as meaning the emulation of a factory system, with all of the associated dynamic processes, in an experimental model. The goal is to get as close as possible to reality so that know-how obtained from the simulation can be transferred to reality, in other words the real factory (see Bracht, Geckler, Wenzel 2011, p. 318). Autodesk® Factory Design Suite is a comprehensive software package that has been well received in the industry and which was written especially for the virtual development of layouts for production lines and complete production facilities (see Figure). This allows the complex process from planning the building, through the actual installation of the production facilities, right down to planning the progress of the building work and transport routes, to be simulated. The suite extends the operational procedures in AutoCAD® and Autodesk® Inventor® with interoperable procedures that are only available in the suite as well as factory-specific components and content. It therefore improves efficiency, accuracy and communication in factory planning projects as well as flexible reactions to altered business requirements. The Autodesk® Factory Design Suite accelerates factory planning through extensive special commands and a specific environment for the rapid development of factory layouts. Any model can be dimensioned and edited as necessary with the aid of intelligent plant objects such as walls, doors and prop grids. By integrating scatter plot scans, the as-is condition of a plant (hall planning) can be recorded in 3D and then converted or adapted to the virtual environment. Complex conversion work or retrofits can hence be carried out on a 3D layout with the optimum efficiency, quality and flexibility. Analyses of material flows, machinery utilisation and energy consumption are possible in the early engineering and design phases. Non-value-creating costs that are incurred through superfluous transport routes within the factory can be determined on the basis of several simulation scenarios and optimised directly in the 3D layout.

What makes the suite special is that a variety of plant, building and machinery manufacturer data can be managed and compiled in one model. The functions for a digital check and evaluation of the equipment as well as for collision detection and distance analysis thus allow a custom-fit construction of the factory geometry before any extensive investments have been made (see Autodesk® 2012).

OUTLOOK

The example of suppliers for the automotive industry shows just how urgent it has become to address the topic of a 'digital factory'. The closer a manufacturer and supplier work together, the greater the pressure to resort to a comprehensive IT solution such as the Autodesk® Factory Design suite. Digital planning, 3D-CAD models, simulation, the compilation of data in a factory model and standardised data exchange are important requirements for this development. Tomorrow's 'digital factory' will also call for an even greater exchange of process data, a topic that is still new for many companies outside the core zone of automobile production, but which is already possible today with the Autodesk® Factory Design suite (see [START_REF] Autodesk® | Digital factorya topics for SMEs?[END_REF].

The topic of the 'digital factory' as well as the associated AS-IS analysis and efficient 3D layout planning during the conversion of old and design of new production facilities by means of 3D-CAD will also have to be dealt with in different forms by small and medium-sized enterprises. N+P links individual software products and offers an overall, customer-optimised IT solution for factory development and planning, thus creating added value, efficiency and a cutting edge for the customer.

CONCLUSIONS

Optimize your factory layout before it becomes real. Autodesk ® Factory Design Suite helps you to design and communicate the most efficient manufacturing layout by creating a digital factory model. Evaluate quickly multiple "what-if" scenarios to determine the best solution before any equipment is installed. Factory-specific visualization and analysis tools are helpful by increasing innovations, design efficiency and communication.

Fig. 1 .

 1 Fig. 1. -From 2D layout planning to 3D layout planning with the Autodesk® Factory Design Suite (Autodesk 2012)


Franz E Gruber
email: franz.gruber@forcam.com

Industry 4.0: A Best Practice Project of the Automotive Industry

Keywords: shop floor, automotive, sensors, best practice, FORCAM

FORCAM provides the industry with innovative production software technology (Factory Framework™) and consults on state-of-the-art shop floor management. World class companies from diverse manufacturing sectors like automotive, machinery, aerospace, medical engineering and packaging are utilizing FORCAM's shop floor management solution.

Introduction

It is worldwide known and accepted that FORCAM provides the industry with innovative production software technology (Factory Framework™) and consults on stateof-the-art shop floor management. World class companies from diverse manufacturing sectors like automotive, machinery, aerospace, medical engineering and packaging are utilizing FORCAM's shop floor management solution. It enables companies to measure performance of their machines and plants in real-time to quickly recognize and correct errors and waste, and to continuously optimize their productivity.

FORCAM advantages and results

With

From the operator to the manager

All roles involved are able to continuously optimize productivity within their role.

Leading-edge Technology: Complex Event Processing (CEP) with Live Cache FORCAM uses Complex Event Processing (CEP) with Live Cache, a technology used for real-time analysis of event stream from the financial sector. FORCAM combines CEP with the proven and tested MES in a rule-based approach in an optimal way.

Conclusions, Results

 Fast reaction with latencies in the millisecond range and high throughput (factor is 100 times higher than in the past product generation)  Rule-based approach enables flexible, user-defined functions  Global deployment potential with Unicode language support and centralized server architecture

3

  At FORCAM, we value TRUE OEEWith the help of FORCAM, elite companies have been able to increase productivity measured with TRUE OEE by up to 25% within the first year.The Recipe for Success -holistic Shop Floor Management that effectively combines the most advanced Shop Floor Management System with the Lean Management philosophy.A Recipe for Success in Shop FloorManagement:  Measuring REAL OEE -what you cannot not measure you cannot improve  Adopting Lean Management principles and lead by OEE  Creating a Continuous Improvement Process (CIP) organization with closed-loop communication  Delivering the right information to right people at the right time  Delivering planned vs. actual information to shop floor operators  Establishing a PDCA (Plan-Do-Check-Act) cycle with actions and measures  Setting regular TRUE OEE goals for continuous improvement Advanced Shop Floor Management creates the Transparent Factory. Measuring and optimizing the performance of manufacturing plants in real-time FORCAM provides the industry with innovative production software technology Factory Framework™ and consults on modern shop floor management. Leading companies from diverse manufacturing sectors like automotive, machinery, aerospace, medical engineering and packaging are utilizing FORCAM shop floor management solution. It enables companies to measure performance of their machines and plants in real-time to quickly recognize and correct errors and waste, and to continuously optimize their productivity. Planning and Production are now synchronized "Nowadays, companies need resource efficiency in processes and in the manufacturing." FORCAM's Chairman, Franz Gruber, states. Everything has to intertwine in a way that errors and waste can be recognized immediately and eliminated sustainably. The FORCAM technology complements standard ERP-software on the planning level (top floor) using objective performance data coming directly from all factory assets (shop floor)from one single machine to multiple plants worldwide. The efficiency factor of standard ERP-software is enhanced due to the real-time data capture by FORCAM. Concurrently, FORCAM enables customers to apply the technology themselves in their company following a pilot phase. 6 State-of-the-art Shop Floor Management Flexible web-based connectivity of a diverse number of machine controls FORCAM's Factory Framework™ solution is technologically leading Manufacturing Execution System (MES). It enables improvement processes on all levels of the production. Factory Framework™ connects, collects, and standardizes real-time data from most different machine controls. For every production level, the signals provide comparable web-based operational states of machines and plants (production, malfunctions, and downtimes). Result: Transparent and reliable performance dataruntime, speed, quality. Additionally, Factory Framework™ connects production data with ERP data from corporate planning such as targets for orders and resources.

Overall Equipment Effectiveness is optimized OEE -Overall Equipment Effectiveness

Shop Floor Management (SFM) is a strategy designed for the continuous optimization of the plant availability by eliminating errors and waste. The most important key figure to measure the performance is the OEE -Overall Equipment Effectiveness.

 OEE is the most important key figure (KPI) to implement the SFM strategy.  OEE is the measure for the added value of a machine.  OEE visualizes exactly which machine and process losses can be minimized.

OEE -Three crucial performance metrics: Availability, Productivity, Quality

As key performance indicator, OEE results from three performance data which FORCAM monitors and visualizes in real-time, and therefore available anywhere and at any time:

 How long has it been producing?  How fast has it produced?  How well has it produced?


Dr Arndt Richter

Economic Advantages by CAD/CAM Use in Compound with Production Data Organization

Keywords: CAD/CAM, multi-task machine tool, automatic feature recognition, 3-5-axis-milling, virtualization, simulation, tool management, production data management, blank part actualization, tool sequence optimization, 3D tool models, production resources, communication platform 1

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INTRODUCTION

In the manufacturing industry a highly interesting upheaval takes place presently. Not only new production means with new technical possibilities, modified production structures with out-or insourcing or whole production transfer to other production areas, but especially also new approaches for the networking of information about the complete production operations is meant. These new approaches, also summarized under the slogan Industry 4.0, will allow among others  the further growing together or the parallelism of product development and product design processes  the better linkage of virtual and real world of the production as well as  the penetration of the communication in all areas of planning, preparation and execution of the production.

Thereby the digitalization of the production sequences turned out as one of the greatest driver of innovation. The constantly improving junction of the virtual and real production will increasingly be important for an efficient production. Therewith also for classical processes of production planning, e.g. CAD/CAM planning or production data and tool management new tasks arise, which only lead to a better economic representation in interaction of all components. CNC-controlled machine tools always require digital data, that means digitized geometry, technology and organizational data as input for the machine tool control. In the course of the development powerful CAD/CAM systems originated from the simple NC programming, which include under the aspect of the overall system machine tool -clamping device -tool -workpiece extensive planning functions. But for the efficient use of these systems more and more digital data of the process control, production means and production resources are required to create safety and reliable results. Systems for the production organization as PLM-, tool management-or MESsystems have been established parallel to the geometric and technical oriented CAD/CAM systems. All systems require similar, partially equal data concerning the content, to generate the demanded planning results. The required data are managed locally and in general not compatible because of different development approaches and development targets. From the point of view of an economic production the great challenge is to obtain the continuity and consolidation of the organizational and technical oriented systems

CHALLENGES FOR CAD/CAM SOLUTIONS

The requirements of the manufacturing industry concerning the CAD/CAM systems are very versatile and characterized by different factors.

In the machine tool sector currently dominate especially multi-task machines, which enable a mix of processes in many different ways. Therewith it is possible to machine workpieces completely on one machine. However, this causes a more and more complex kinematics of the machine tool and in the large machine tool construction the increasingly dominating influence of change-over units like angle heads, facing heads etc.

Directly associated with the development of the machine tool sector are the innovations in the field of tool technology. New production engineering and production strategies can be realized with according modern tools. Examples are High Speed Cutting or High Performance Cutting, but also adaptive machining strategies and combined procedures, e. g. of classical cutting methods in combination with laser-use.

On the other hand new production organizational strategies have been established in the production. An unbroken change from the batch production "on stock" to a client-specific production as well regarding the order number as also the constructive specification can be recorded. Therewith associated are always smaller batch sizes or piece number 1, whereby the efficient single production gets the primacy. Under this aspect preformed workpieces can only be used in a limited way, whereas the machining "from one block", e.g. also the production of prismatic parts from bar material, is becoming increasingly important.

From the mentioned strategic developments in the production and organization area permanently new changing and more extensive challenges result for the CAD/CAM planning. So e. g. the rate of material removal increases permanently and as a result the expenditure for planning, preparation and program generation for the CNC machine clearly increases. The complexity of programming tasks is also growing. The expenditure per program and the number of necessary NC programs per time unit continue to rise drastically and therewith also the CAD/CAM planning is asked to gain more efficiency.

In addition to the pure technical program generation also the requirements concerning the reliability and safety of the created results and the documentation of the planning results increase continuously. Only with clearly improved and more efficient planning methods the requirements from complex production systems can be realized with the requested quality.

Because of the reduction of batch sizes the start-up time increases also drastically in relation to the entire production time. It is required that additionally to a fast and flexible program supply for the machines all necessary production-relevant documents and information are provided reliably. Only this way it is possible to reduce the start-up time drastically. The requirement to minimize the start-up time is emphasized because the low batch sizes require an enhanced flexibility in the production. This has also an impact on re-planning in the production engineering which has to be realized CAD/CAM system supported. A corresponding system support enables to realize the requirements regarding a flexible production with low batch sizes.

Current and future production facilities cannot be seen without a look to the overall organizational process in the factory. Essential requirements to CAD/CAM systems arise because of these integrated considerations from the product development to the CNC machine including the data, resource and quality management. The integrated consideration of all areas is decisive for a successful economic production.

TECHNICAL ASPECTS

The NC preparation has to react fast and flexibly to the often changing requirements from the manufacturing. The results have to be provided with high safety so that the following process steps can be created reliably. For that current CAD/CAM systems offer an lot of possibilities so work fast and efficient. 3D-CAD workpiece models, designed regarding the production technical aspects, are the starting point. This statement is important because for an integrated CAD/CAM planning the responsibility for the measure is based on the CAD model. Therefore pure 3D visualization models of workpieces are not suitable for production engineering. Using an automatic, in modern CAD/CAM systems integrated, feature recognition the required parameters for the production-oriented processes can be determined quickly. Accordingly adapted systems provide very quick and flexible nearly fully automatic results for an efficient production this way (fig. 1). Thereby it is important that in addition to standard sequences respective customdesigned machining strategies can be stored to guarantee a know-how protection and also individual company-specific sequences.

For the complete machining of a workpiece with several machining steps in terms of a mix of process with turning, drilling and milling of 2 -5 axes a dynamic blank part actualization is indispensable. For each machining step the current blank part has to be provided to plan the following machining step with the current geometry data (fig. 2)

Fig. 2. -CAD/CAM planning with blank part actualization in all processes steps

Because of the complexity of the workpiece geometry and the production requirements resulting therefrom it is more and more necessary to use additional sets on machine tools . Only this makes it possible to realize the geometric and qualitative machining requirements. In the large part manufacturing sector such change-over units are absolutely essential, because a relocating of the workpiece is extremely complex, so that the total workpiece has to be machined with one or two settings as possible. The use of different angle heads, facing heads etc. is the rule. Large machine tools have additionally different parallel axes so that the tool can approach to the machining point efficiently. For the CAD/CAM planning such machine kinematics are special challenges. Not only the pure machining has to be regarded and the tool paths to be generated but especially the entire question of the use of aggregates have to be considered. This is the consideration of the tool and attachments handling here, especially the head positioning and the head change. A further emphasis is in this context the tool sequence optimization over several machining sides including the use of change-over units.

Beneath the organizational handling of change-over units including the handling of perhaps changing coordinate systems for the several machining sides of different aggregate applications the visualization of the complete process has the highest priority. For the simulation of the machining sequence it is differentiated basically the tool path-related simulation and the machine simulation based on the NC codes. EXAPT has the target to provide a respective detailed simulation already in the planning of the several process steps. This tool path-related simulation including the display of the kinematics of the machine is completed by a removal simulation with integrated collision control, so that the user gets a largely realistic display. The advantage of the immediate visualization of each machining step during the planning stage is that subsequently no corrections have to be made. Basically both simulation strategies complement one another and lead, at correct application, to high efficiency in the production. All aspects of change-over units have to be regarded and visualized in the case of tool path-oriented simulation, naturally. Especially the Placing of the attachments to the workpiece for the processing and the collision check of the attachments with the workpiece, the clamping devices and other machine elements are important (fig. 3).

Fig. 3. -Simulation of the machine environment based on tool paths

The specific challenge to CAM systems is for this simulation strategy in the planning phase not only to simulate machine motions but also to display transfer motions of the machine tool e. g. concerning the tool or aggregate change, where the tool is not used. The current EXAPT developments have set broad standards in this area. The entire kinematics of the machine tool can be displayed because of the integration of all movements, also the passive machine movements in the processor, and the range of functions of the postprocessor can be reduced explicitly (fig. 4).

ORGANIZATIONAL ASPECTS

Regarding the described complex manufacturing procedures in detail it quickly becomes clear that beside the physical specification of the system machine tool -clamping device -tool -workpiece also the organizational states of the production resources are eminently important. Therewith especially the tools move into the focus.

In addition to the pure technical description of the tool and especially of the cutting edge also the geometric specification of the assembled tool as a 3D model is required for a safe technology-oriented production planning. This is the condition for a safely collision control and an objective visualization of the entire process. There is a need to distinguish in general that concerning the tool geometry has to be differentiated between a physical and a technological tool model. This quickly becomes clear for asymmetric rotatory tools as boring bars (fig. 5).

The technical description of the tool essentially determines the accuracy and therewith the quality of the planning process. Important economic effects are developed additionally by a corresponding organization of the classic tool department. This are not simply questions e. g. of the storage of tool components or the pre-reservation of special tools for the machining but especially the tool logistic and the job oriented scheduling of tool deployment on the shop floor. Scheduling of tool deployment thereby comprises the whole process from the tool selection in the CAM process via the generation of orders and the provision of tool data for tool presetting machines up to the transfer of the necessary data to the machine tool. A significant reduction of set-up time can be reached by combining several tool setting orders with an according sequence optimization of the production orders. Thereby the savings are not only in the machine area but also in the tool presetting area, because fewer tools have to be set. Savings up to 30 % of logistic time for tools in relation to normal processes can be verified with this solution. In the comparison between the real set-ups state on the machine with the planned set-up orders are further effects which can be realized with an online communication to the machine tool.

Geometry model

INTEGRATED DATA CONCEPT BETWEEN TECHNIQUE AND ORGANIZATION

The above-mentioned statements clarify that at every point of the process planning safely and reliable information of the state of the production means and production resources have to be available. Considering only one side of the planning tasks the positive results are ruined by other negative influences. Therefore it is necessary to create a corresponding communication to enable the provision of the relevant data in every process step. This is the only way to ensure that the planning results really correspond to reality. Beside reliability and completeness of the required technical characteristics an according communication platform is extremely important (fig. 6). This communication platform does not only have the function e. g. to exchange data between a CAD/CAM and a tool management system but has to consider the entire process. All partners participating in the entire process have to be addressed by suitable communication techniques, e. g. WEB-based solutions, and to be integrated into the general communication. In the area of tool logistic this refers to the questions of communication with different storage systems, the mobile tool identification, the tool presetting or the communication with NC controls. Only this complex logistic consideration makes it possible to obtain the economic effects resulting from this solution. But it is also clear that a corresponding dovetailing of the information is absolutely essential today. With the EXAPT production communication manager EXAPT provides a system which manages a browser-oriented uncomplicated communication with the several stations in the shopfloor. Additionally it is possible provide all production relevant information via respective techniques at every place. Therewith according process sequences can be created more transparent, information can be exchanged immediately and bottlenecks can be displayed transparently more quickly, if necessary.

CONCLUSIONS

It can be seen that an economic CAD/CAM-use requires a high technological performance of the system combined with according simulation techniques for the visualization and control of the results, but additionally the compound to the organization, especially to the tool management, are indispensable. Due to the close connection of CAD/CAM and organization the economic success can be realized, especially in terms of small run and client-oriented production. Thereby it is not a matter of point to point connections but by building a communication platform the matter is a strategic orientation of the whole communication technique inside a CAD/CAM compound.

Fig. 1 .

 1 Fig. 1. -Automatic feature recognition with automatically generated and client-specific extended machining

Fig. 4 .

 4 Fig. 4. -Large machine tool with tool and attachment change

  Fig. 5. -Appropriate tool data for the NC production

Fig. 6 .

 6 Fig. 6. -Technique, organization and communication in the area of the CAD/CAM system