The high voltage transmission business uses very mature technical solutions to transport electrical energy over large distances. New developments in the information technology sector are now promising opportunities to revolutionize the traditional processes within the business. In this paper the opportunities to implement a sophisticated knowledge infrastructure to improve the efficiency and quality of high voltage product manufacturers will be outlined. Therefore, possible solutions have been assessed to establish a non-redundant data structure and create an advanced database system architecture with respect to business specific requirements, considering in particular product configurators. Based on the proposed master data system, the possibility to create as well as integrate a knowledge system has been evaluated. Accordingly, the introduction of a global knowledge manager is proposed to organize inquiries of product configurators to expert systems and introduce a company-wide framework for rules and constraints. To assure communication between all parts of the software architecture, the implementation of a universally understandable format is discussed. Finally, possibilities to integrate recommendation system mechanisms into the suggested system architecture are highlighted.
The market of high voltage transmission business is highly competitive. The differentiation through up to date processes, high quality and fast response times is highly desirable to manage the increasingly complex and fast changing customer requirements. This effect is intensified by general technical developments in measurements initiated by the energy transition from fossil to renewable energy sources.
Due to an increasing share of renewable energy into the grid and
their decentralized physical arrangement compared to huge power
plants, an extension of the electrical grid has to be provided.
Additionally, the weather dependency of the new energy sources
intensifies this effect. As a result, the utilities are confronted with a
fast changing energy market and need to react to the new energy
mixture [
To tackle the above described challenges, the introduction of a well-designed data and software infrastructure is necessary. A completely integrated data and software landscape which provides necessary information via interfaces to all quotation related tools should provide synchronization of all involved stakeholders and improve the maintainability of data and knowledge.
In an environment which utilizes several ERP (enterprise resource planning), PDM (product data management) and CRM (customer relationship management) tools, in future one company-wide integrated database should be implemented to deliver one data source for all configuration, pricing and quotation tools. The goal is to enter the information only once into the system so that the characteristic is passed on to all connected business segments and their CPQ tools. In consequence, all related objects rely on the same data input. This assures cross segmental consistency of data in all offer documents, technical descriptions and technical calculations.
Moreover, the integrated representation of data delivers the opportunity to implement consistent connections between objects in form of rules and constraints. This leads to the extension of data to knowledge and should support users by preventing false configurations and incorrect data input, i.e., to contract relevant documents. These relations between the objects need to be nonredundant as per the data itself. Supplemental to the rules and constraints describing simple relationships, interfaces to expert systems capable of very specific and complex calculations need to be established. Mechanical calculations due to earthquake requirements or ferroresonance calculations of the grid are two examples of these expert systems.
Finally, based on the achieved integrated data and knowledge, an analysis of the utilized materials, parameter characteristics and all other objects during the configuration, prizing, and quotation process can act as a basis for a self-learning system to improve the CPQ-tools. This system should be able to recommend technical solutions and parameter input based on previously chosen solutions in distinctive situations as customer specific requirements or special environmental conditions. The user in this scenario still has the opportunity to neglect the recommended solution which is consequently used to improve the recommendation logic. Overall, a complex system composition consisting of domain specific and integrated databases with direct interfaces to configuration, pricing, and quotation tools has to be established. Further, the user of the quotation tools is supported by knowledge bases inheriting logical connections between relevant parts and an adaptive artificial intelligence which analyses user decisions. The remainder of this paper is organized as follows. In section 2 we discuss the possibility of a holistic database and point out that different use cases lead to contradicting database types. Conducted from this perception we propose system architecture assuring data consistency for the high voltage transmission business. Based on this data consistency section 3 emphasizes the advantages of knowledge integrity. This is followed by a general survey on an approach to implement a global knowledge manager on basis of the proposed system architecture in section 4. Section 5 suggests a concept of a recommendation system in which the knowledge base is constantly extended using the results of configuration applications used by experts.
Data modelling plays an important role. To create a ubiquitously
applicable database, one has to consider a data structure which
allows multiple views and possibilities to manipulate the stored
data via interfaces from manifold applications. Graeme C. et al.
characterize this situation as follows ‘The data model is a relatively
small part of the total systems specification but has a high impact
on quality and useful life of the system’ [
Typically used database types are relational databases (RDBs),
object-oriented databases (OODBs) and a hybrid form which is
called object-relational database (ORDB). Consistency in RDBs is
achieved by using normalization methods for tables as proposed in
[
User type Content Whereas ERP, CRM, and PDM tools are designed for fast access to distinctive data to satisfy operational queries, CPQ and expert systems are focused on very complex queries that require combinations between many data sources. Additionally, CPQ-tools are facing a high access frequency with expected short response times which leads to an even higher level of complexity in the data structure.
In conclusion, based on these manifold requirements it seems more likely to implement a sophisticated system architecture including several customized databases for each application instead of establishing one ubiquitous database. The system architecture of such a conglomeration of databases is closer examined in the next chapter.
The data used along the value chain can be described most likely as
‘master data’ of a company. Master data is defined as ‘data held by
an organization that describes the entities that are both independent
and fundamental for that organization, and that it needs in
reference in order to perform its transactions’ [
Decentralized data creation and maintenance approaches on the other hand rely on company-wide standard definitions (3) or an implementation of a repository (4). Company-wide standards do not assure consistency in each dataset of the applications. Instead they focus on the ability to create the same understanding of each attribute which leads to easier manageable comparisons between those datasets. A physical connection between applications is in this approach not mandatory. The installation of a repository follows the idea of metadata storage to connect applications with each other whenever an interaction is necessary. Therefore, primary keys of all involved applications for a certain attribute are stored in the repository and matched for cross-program query events with each other.
In case of the high voltage transmission business, an
implementation of one integrated MDM solution seems, equivalent
to the result of the second chapter for databases, not feasible. Two
reasons are mainly responsible for implementation of a more
complex structure. First of all the structure of the business
includes, as already pointed out, several different independent
departments responsible for distinct parts of the substation. These
departments are not necessarily located at the same location but are
distributed over the world to assure an increased satisfaction of
locational requirements. Consequentially, one centralized system
located, for instance, in Europe will lead to performance issues
when it comes to queries from an application located in Asia. Live
connections over long distances and many servers are due to the
congestion control of the transmission control protocol not
advisable [
Figure 3 shows an option where a centralized master data system is implemented storing master data of one manufacturing location whereas the centralized database is connected to other locations via a repository to assure a synchronization of all business relevant data independent from daily operational tasks. Furthermore, standards across the whole company are defined to realize a homogenous creation of new data since each master data system is allowed to create and maintain its data by itself. In another scenario a company-wide leading system located in at a distinct place is established to create and maintain all master data. This leading system is additionally used as basis for connected central master data systems installed in distributed factories of the company. These centralized master data systems receive the company-wide master data from the leading system and can be extended with manufacturing side specific master data as basis for connected applications. Further combinations are imaginable as well and have to be evaluated based on several reference values in further publications. Based on these results and taking all requirements for the high voltage transmission business into account finally a decision on the system architecture can be reached. Another important decision is the selection of the tool used as master data management system. The use of the ERP, CRM or PDM tool is imaginable since the most data is created in these databases. Additionally, the adaption of the CPQ-tool as main input tool for data might also be a reasonable choice.
Up to that point we focused on data structure and system architecture neglecting the value which can be created out of integrated, non-redundant data. The following chapters will discuss the possibilities given by such a dataset. 4
A well-known use case for master data management systems is the
implementation of data warehouses. Operational data is put
through an ‘extraction, transformation, integration, and cleansing
process (to) store the data in a common repository called data
warehouse’ [
The restriction of this concept is already given in the definition of
the data warehouse. The data warehouse should ‘support
management’s decision making process’ [
Another issue which is more and more visible to companies arises
with the implementation of more than one configuration software.
Since the beginning of the new millennium a rising number of
companies implement product configurators to treat a phenomenon
called ‘mass customization’ [
This technology was immediately adopted by the high voltage transmission business since the modular design of its products is predestinated to realize product configurators. Unfortunately, the degree of standardization in the business does not allow a full switch from CAD (computer aided design) applications to product configuration solutions. Special-purpose solutions define the high voltage transmission market up to fifty percent. The result is an increasing redundancy in the configuration data and knowledge. While the CAD system inherits engineering data accomplished by rules and constraints for the product with a high degree of freedom to support the engineering expert, the product configuration application is designed for sales people or even for the customer and includes a separated engineering dataset complemented by even more sophisticated rules, constraints and methods to prevent a wrong configuration. Nevertheless, a redundancy of engineering data and knowledge is introduced; leading to a high maintenance effort and complicated processes whenever the research and development department (R&D) releases technical innovations or the product lifecycle management department (PLM) disables the use of certain parts of the product.
Based on these evaluations, a centralized engineering database has
to be implemented as foundation for all product configurators.
PDM systems fortunately inherit all relevant product information
and can, as the major tool for PLM and R&D departments, be
utilized as a centralized engineering database. The result is a
database valid for all configuration applications which are no
longer maintained decentral by each product configurator but are
centrally maintained by the product responsible departments. The
technical realization of this requirement can be established by
introducing interfaces between the product configurators and the
PDM system. However, with this step an integrated data
administration can be introduced but the knowledge administration
is still redundantly managed in each configuration tool.
To achieve knowledge integrity - a major target formulated in the
visions at the beginning of this paper - we propose steps connatural
to the actions necessary to reach data integrity [
An initial approach to set up a system architecture analog to the
requirement formulated above was made in the paper ‘On
Knowledge-Base System Architectures’ and is illustrated in Figure
5 [
A user of CPQ-tool 1 is in consequence not allowed to choose product A if the rated current exceeds 2500 A and an ambient temperature of 35°C is given. Contradicting to this rule, an expert in CPQ-tool 2 is not restricted by this constraint. An expert could decide to use product A if the current exceeds 2500 A at a ambient temperature of 35 °C knowing that the conductor is allowed to exceed 65 °C if the conductor is not touchable by humans. This expert knowledge includes besides product knowledge as well knowledge about spatial constraints and human interactions with the product and is with its complexity not easily describable in a non-expert configuration tool. Nevertheless both configuration systems will lead to a correct solution. CPQ-tool 1 will lead to the costlier product B but is operable by the customer herself while CPQ-tool 2 with a higher degree of freedom will deliver a cheaper solution of the configuration task but needs expert knowledge. Therefore, two options for the customer are established, a slightly costlier but very fast configuration or a very accurate solution with a more time consuming configuration. Location 2 is in detailed visible in Figure 8 and includes the standard databases, CPQ-tool 1 and an expert system. The previously mentioned configuration task to calculate the mechanical forces on a circuit breaker in case of an earthquake is given. This calculation task requires information which is not stored in the PDM database or any other standard available master data. Additionally, very specific calculation methods have to be applied not handled in the CPQ-tool. An expert system is necessary to solve the calculation task. The calculation inquiry is sent from the CPQ-tool via the universally understandable format to the GKM that interprets schedules and finally processes the request to the correct expert tool. In consequence, the GKM inherits besides generalized rules and constraints also information about the expert tools in the system and administrates access to them. The inquiry is handled by the expert system using the information received via the interface and by utilizing additional information like specific knowledge on the occurring earthquake forces in the concerned region to calculate the forces on the circuit breaker. The result is processed back to the GKM and further to the CPQ-tool where the resulting values trigger rules and constraints to decide which circuit breaker has to be chosen. These two simplified examples are only supposed to give an overview about the working-principle to be established with the introduction of a GKM and need to be further researched in following publications. But since the vision formulated at the beginning of this paper also includes recommendation mechanisms and possibilities to implement self-learning algorithms the proposed system architecture needs to be accomplished by continuative considerations. 6
Recommender systems are since the 1990s an increasingly used
service in mainly e-commerce applications to recommend simple
products to users [
Besides the possibilities given for e-commerce sellers, a second very large field of application opens with the usage in expert systems. Mainly product configuration applications are adopting recommendation techniques which can be classified in: 1. 2. 3. 4.
collaborative recommendation – relying on the choices made previously by other users with the same social and demographical background content-based recommendation – relying on choices made previously by the user herself knowledge based recommendation – relying on user requirements and domain knowledge hybrid forms – try to combine the other types to avoid disadvantages of each stand-alone solution With respect to the high voltage transmission business the only reasonable choice for recommender systems is the knowledge based recommendation technique since electric power transmission substations do not rely on choices or preferences of single users but on very detailed requirement specifications delivered by the customers (utilities). Even if the requirement specifications of utilities do not change frequently and a content-based recommendation could be possible in terms of parameter input to a configuration application an important circumstance, a unique feature of substations has to be taken into account – the environmental conditions. Unlike other typically configurable products like cars or kitchens substations are crucially impacted by the locations they are assembled.
For example, the Russian ministry of electricity announces in a tender a high voltage transmission substation with the same topology (electrical circuit diagram) and electrical requirements as five years before. One might conclude that the same electrical requirements lead to the same bill of material and same physical topology of the substation. But taking the new location near the Baltic Sea compared to the previous one in Novosibirsk into account this paradigm is false. The environmental conditions including temperature, air pollution, earthquake requirements and altitude of side have an essential impact on the physical arrangement of the substation. This set of conditions to be considered can be depicted as a very complex conglomeration of constraints and is in conclusion applicable for recommendation systems. However, the complexity of the configuration task is probably too high to be provided with all features in one product configuration application which is why the example in the previous chapter has been chosen.
To achieve the best configuration solution many specialized systems have to give input to the configuration process. Mechanical calculations, waste heat, ferroresonance and further calculation applications are delivering valuable information and need to be addressed to receive a feasible solution. The expert systems outcome is involved as input for the existing recommendation constraints to create a solution for the given configuration task. The user of CPQ-tool 1 in the example illustrated for Figure 7 as a non-expert gets one feasible solution recommended without any repair mechanism. The solution will be rather conservative, but is in line with the given rules and constraints. On the other hand the expert using CPQ-tool 2 in the example has the possibility to neglect the recommended solution and choose a more efficient one. The changes are recognized by the system and adapted to the existing constraints in the GKM. A self-learning system as formulated in the vision at the beginning of this paper is created using expert knowledge to continuously improve the general knowledge manager as a basis for all product configurators. Basis for this mechanism is the system architecture and universally understandable format to provide communication and non-redundancy between all parts of the system as proposed in this paper. 7
The paper discussed the currently arising challenges and opportunities given in the high voltage transmission business and highlighted the current situation of the information technology in the business. Insulated solutions due to complexity of the products and the world-wide distribution of the associated business segments lead to redundant data storage and the development of several different product configuration solutions. On the basis of the state of the art methods to normalize data and to integrate master data solutions into the system, considerations concerning the resulting system architecture have been made. Furthermore, the need to create a non-redundant knowledge set has been emphasized in addition to a normalized and integrated data set. Deducted from this condition, the proposed system architecture was extended by introducing a global knowledge manager on the same level as the master data system to create a framework for configuration, pricing and quotation rules and constraints. Additionally, a universally understandable format was proposed to enable communication between all parts of the system and to create the possibility to integrate expert systems via inquiries scheduled and processed by the global knowledge manager. The working principle of this system was outlined by two examples. Finally, the opportunity to extend the system by recommendation techniques and self-learning algorithms was pointed out.
Since this paper was supposed to give only a first overview over the problem statement, several future prospects arise from the evaluations presented. These future prospects are the following: ∂
Data integrity – how can product configurators be enabled to use data from centrally maintained databases instead of using encapsulated exclusive data sets resulting in redundancy? ∂ ∂ ∂ ∂ ∂
Knowledge integrity – how should knowledge normalization methods look like to build the base for a global knowledge manager and a framework for rules and constraints? System architecture – which system architecture allows the highest performance, best maintainability, and security with respect to the requirements given by a fully integrated knowledge system? Global knowledge manager – how should the global knowledge manager be designed? Universally understandable format – how should a format look like which is processible by all databases and programs in the system, including expert systems and product configurators? Recommender system – how can rules and constraints be improved by analyzing decisions of experts in a product configurator to improve the recommended solutions to non-experts?