Method and system for managing templates for project engineering

Abstract

A system 200 and a method 100 for managing templates for project engineering. The method includes displaying a series of questions related to industrial automation service associated with the project engineering and receiving an input for question of the series of questions. Each succeeding question in the series of questions is automatically adapted based on the input to the question. The method includes determining keyword from the input and an objective associated with the project engineering; determining template from a template database (210) based on a matching of the keyword and generating the determined template in an exportable format based on user selection, for the project engineering.

Description

[0001] METHOD AND SYSTEM FOR MANAGING TEMPLATES FOR PROJECT ENGINEERING description

[0002] The present disclosure relates generally to creating templates for project engineering, and more specifically to a method and a system for managing templates for project engineering based on an adaptive questionnaire.

[0003] Industrial Automation has changed the world of manufacturing with rapidly expanding a range of applications. Efficiency at which industrial automation systems can be designed, programmed, and installed is lagging the pace at which the industrial automation systems themselves are improving. Generally, engineering and commissioning of the industrial automation systems is a complex and time-consuming process. It requires experts with knowledge of the industrial automation systems and high manual engineering efforts for every adaptation step. Also, a high degree of redundancy exists between the designs of components for unrelated projects. This redundancy can be caused by industry specific, customer specific, and / or application specific requirements.

[0004] This is not desirable, as all the above-mentioned mechanisms are highly time consuming making the process tedious and cumbersome. In a scenarios when there is a requirement to generate different templates in large numbers the existing methods of managing the templates may be inefficient and cumbersome.

[0005] In light of the above, there remains a need for an improved method of managing the process of generation, retrieval and usage of templates for the product engineering in an improved and timely manner.

[0006] The present disclosure seeks to overcome the above-mentioned challenges by an assisted personalized solution suggestion mechanism which reduces engineering efforts. The present disclosure provides a method of managing templates used for engineering and commissioning of industrial automation system using an adaptive questionnaire mechanism. The adaptive questionnaire mechanism ensures that the user needs to answer minimal questions to arrive at an appropriate template, quickly.

[0007] The object of the present disclosure is achieved by a computer-implemented method for managing templates for project engineering. The method includes displaying a series of questions related to industrial automation service associated with the project engineering. The user can then provide their inputs to the series of questions. Each succeeding question in the series of questions is automatically adapted based on the input to the question using machine learning (ML) technique. Therefore, as and when the user starts answering the questions the following questions are adapted accordingly based on the user’s answers. The method also includes determining keywords from the input and an objective associated with the project engineering. These keywords are then used to determine a matching keyword from a template database. Once the matching keyword is found from the template database then a corresponding template associated with that keyword is recommended to the user. There can be multiple templates which can be populated to the user and the user is allowed to select an appropriate template from the list. Further, the user is also provided an option to personalize the template to suit their project engineering requirement. The final template is then generated in an exportable format.

[0008] In one or more embodiments, the method further includes receiving at least one parameter for personalizing the determined template and generating a new template based on the personalization of the template. Further, the method includes storing the new template in the template database.

[0009] In one or more embodiments, the template comprises specification for the project engineering defining the at least one industrial automation service to achieve at least one manufacturing goal.

[0010] In one or more embodiments, the template database comprises a plurality of templates and wherein each template of the plurality of templates is mapped to a plurality of keywords.

[0011] In one or more embodiments, each template of the plurality of templates is mapped to the plurality of keywords based on parsing of a plurality of parameters and user comments associated with the project engineering.

[0012] In one or more embodiments, each template of the plurality of templates are classified into clusters using decision trees. In one or more embodiments, the series of questions are generated based on the plurality of keywords associated with the project engineering using at least one of an artificial intelligence (Al) mechanism and a machine learning (ML) mechanism.

[0013] In one or more embodiments, the series of questions are ordered based on a priority of the at least one industrial automation service.

[0014] In one or more embodiments, the series of questions are provided on a graphical user interfaces (GUI) that enable user to provide a response to the series of questions.

[0015] In one or more embodiments, the method includes determining the at least one template from the template database based on the matching of the at least one keyword includes matching the determined at least one keywords and semantic labels associated with the input with the keywords and semantic labels in the template database. Further, the method includes generating a list of templates relevant to the industrial automation service from the template database, based on the matching of the at least one keyword and semantic labels associated with the input, and the keywords and semantic labels in the template database, wherein each template in the list of templates is provided with a relevance score and determining the at least one template from the list of templates comprising the highest relevance score.

[0016] The object of the present disclosure is also achieved by a system for managing templates for project engineering. The system includes an interface configured to display a series of questions related to at least one industrial automation service associated with the project engineering. The system also includes a processor; and a memory coupled to the processor. The memory includes instructions which, when executed by the processor, configures the processor to receive an input for at least one question of the series of questions, where each succeeding question in the series of questions is automatically adapted based on the input to the at least one question using machine learning (ML) technique and determine at least one keyword from the input and an objective associated with the project engineering. Further, the processor is also configured to determine at least one template from a template database based on a matching of the at least one keyword; and generate the at least one template in an exportable format based on user selection, for the project engineering. The object of the present disclosure is further achieved by a computer program code which, when executed by a processor, cause the processor to carry out steps of the aforementioned method.

[0017] The object of the present disclosure is further achieved by a computer program product comprising computer program code which, when executed by a processor, cause the processor to carry out steps of the aforementioned method.

[0018] Still other aspects, features, and advantages of the disclosure are readily apparent from the following detailed description, simply by illustrating a number of particular embodiments and implementations, including the best mode contemplated for carrying out the disclosure. The disclosure is also capable of other and different embodiments, and its several details may be modified in various obvious respects, all without departing from the scope of the disclosure. Accordingly, the drawings and description are to be regarded as illustrative in nature, and not as restrictive.

[0019] A more complete appreciation of the present disclosure and many of the attendant aspects thereof will be readily obtained as the same becomes better understood by reference to the following description when considered in connection with the accompanying drawings:

[0020] FIG 1 is a flowchart representation of a computer-implemented method for managing templates for project engineering, in accordance with one or more embodiments of the present disclosure;

[0021] FIG 2 is a block diagram representation of a test suite management system for managing the templates for the project engineering, in accordance with one or more embodiments of the present disclosure;

[0022] FIG 3 is an exemplary depiction of grouping of templates, in accordance with one or more embodiments of the present disclosure;

[0023] FIG 4 is an exemplary depiction of flow of the template generation based on an adaptive questionnaire, in accordance with one or more embodiments of the present disclosure;

[0024] FIG 5 is a flowchart representation of a method of generating the template based on the adaptive questionnaire, in accordance with one or more embodiments of the present disclosure; and

[0025] FIG 6A-6D are exemplary depiction of graphical user interfaces (GUIs) leading to generation of personalized template, in accordance with one or more embodiments of the present disclosure. Various embodiments are described with reference to the drawings, wherein like reference numerals are used to refer to like elements throughout. In the following description, for the purpose of explanation, numerous specific details are set forth in order to provide thorough understanding of one or more embodiments. It may be evident that such embodiments may be practiced without these specific details.

[0026] Accordingly, embodiments of the proposed solution herein are achieved by a computer-implemented method for managing templates for project engineering. The method includes displaying a series of questions related to industrial automation service associated with the project engineering. The user can then provide their inputs to the series of questions. Each succeeding question in the series of questions is automatically adapted based on the input to the question using machine learning (ML) technique. Therefore, as and when the user starts answering the questions the following questions are adapted accordingly based on the user’s answers. The method also includes determining keywords from the input and an objective associated with the project engineering. These keywords are then used to determine a matching keyword from a template database. Once the matching keyword is found from the template database then a corresponding template associated with that keyword is recommended to the user. There can be multiple templates which can be populated to the user and the user is allowed to select an appropriate template from the list. Further, the user is also provided an option to personalize the template to suit their project engineering requirement. The final template is then generated in an exportable format.

[0027] Examples of a method, a system, and a computer-program product for managing templates for project engineering are disclosed herein. In the following description, for the purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding of the embodiments of the disclosure. It is apparent, however, to one skilled in the art that the embodiments of the disclosure may be practiced without these specific details or with an equivalent arrangement. In other instances, well-known structures and devices are shown in block diagram form in order to avoid unnecessarily obscuring the embodiments of the disclosure.

[0028] Conventional methods and systems for template creation creates new projects from scratch or using templates. The templates and Wizards that aids in the project creation exists in some cases, but an assisted and personalized template suggestion with adaptive questionnaire doesnt exist. Unlike to the conventional methods and systems, the proposed solution provides the assisted and personalized template suggestion with adaptive questionnaire which enables the user to arrive at the appropriate template with less effort.

[0029] Unlike to the conventional methods and systems, the proposed solution drastically reduces the project creation time, the manual parametrization in commissioning is also minimized.

[0030] Referring now to FIG 1 , illustrated is a flowchart of a method (as represented by reference numeral 100) for managing templates for project engineering by a system, in accordance with an embodiment of the present disclosure. As used herein, templates can be for example but not limited to design templates i.e., hardware or software design templates. Hardware design templates are representative of generic configurations of one or more hardware modules. For example, if the project requires operation of a flow meter, the hardware design template can include the inputs and outputs (I / O) required for the flow meter, required network connectivity for the I / O points, a determination of whether a control cabinet is necessary, and any additional generic design elements necessary for the operation of the flow meter. Similarly, software design templates are illustrative of generic sequences of events, and handling of exceptions, that can be translated into computer executable commands.

[0031] As discussed, the present disclosure involves providing series of questions to users and determining the input to the questions. Based on the user input to the questions the succeeding questions are dynamically and seamlessly adapted to make the questions more relevant to the requirement of the user. Then keywords are extracted from the input and other sources. These keywords are then used to search for matching keywords from the template database 210. On finding the matching keyword from the template database 210 the corresponding templates which are mapped to those keywords are populated to the user. The user can then select the most appropriate template from the list. Further, the proposed solution also provides the option of personalization of the determined template to suit the user’s requirements. As a result, when the proposed solution is implemented, the user will be able to save time as they can answer minimal number of questions and quickly arrive at the appropriate template. This enhances the overall operational efficiency and speed of the project engineering. Referring to FIG 2, illustrated is a block diagram of the 200 for managing the templates for the project engineering, in accordance with one or more embodiments of the present disclosure. It may be appreciated that the system 200 described herein may be implemented in various forms of hardware, software, firmware, special purpose processors, or a combination thereof. One or more of the present embodiments may take a form of a computer program product comprising program modules accessible from computer-usable or computer-readable medium storing program code for use by or in connection with one or more computers, processors, or instruction execution system. For the purpose of this description, a computer-usable or computer-readable medium may be any apparatus that may contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device. The medium may be electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system (or apparatus or device) or a propagation mediums in and of themselves as signal carriers are not included in the definition of physical computer-readable medium include a semiconductor or solid state memory, magnetic tape, a removable computer diskette, random access memory (RAM), a read only memory (ROM), a rigid magnetic disk and optical disk such as compact disk readonly memory (CD-ROM), compact disk read / write, and digital versatile disc (DVD). Both processors and program code for implementing each aspect of the technology may be centralized or distributed (or a combination thereof) as known to those skilled in the art.

[0032] In an example, the system 200 may be embodied as a computer-program product 200 programmed for performing the said purpose. The system 200 may be incorporated in one or more physical packages. By way of example, a physical package includes an arrangement of one or more materials, components, and / or wires on a structural assembly (e.g., a baseboard) to provide one or more characteristics such as physical strength, conservation of size, and / or limitation of electrical interaction. It is contemplated that in certain embodiments the computing device may be implemented in a single chip. As illustrated, the system 200 includes a communication mechanism such as a bus 202 for passing information among the components of the system 200. The system 200 includes a processor 204 and a memory 206. Herein, the memory 206 is communicatively coupled to the processor 204. In an example, the memory 206 may be embodied as a computer readable medium on which program code sections of a computer program are saved, the program code sections being loadable into and / or executable in a system to make the system 200 execute the steps for performing the said purpose. Generally, as used herein, the term “processor” refers to a computational element that is operable to respond to and processes instructions that drive the system 200. Optionally, the processor includes, but is not limited to, a microprocessor, a microcontroller, a complex instruction set computing (CISC) microprocessor, a reduced instruction set (RISC) microprocessor, an exceptionally long instruction word (VLIW) microprocessor, or any other type of processing circuit. Furthermore, the term “processor” may refer to one or more individual processors, processing devices and various elements associated with a processing device that may be shared by other processing devices. Additionally, the one or more individual processors, processing devices and elements are arranged in various architectures for responding to and processing the instructions that drive the system 200.

[0033] Herein, the memory 206 may be volatile memory and / or non-volatile memory. The memory 206 may be coupled for communication with the processor 204. The processor 204 may execute instructions and / or code stored in the memory 206. A variety of computer-readable storage media may be stored in and accessed from the memory 206. The memory 206 may include any suitable elements for storing data and machine-readable instructions, such as read only memory, random access memory, erasable programmable read only memory, electrically erasable programmable read only memory, a hard drive, a removable media drive for handling compact disks, digital video disks, diskettes, magnetic tape cartridges, memory cards, and the like.

[0034] In particular, the processor 204 has connectivity to the bus 202 to execute instructions and process information stored in the memory 206. The processor 204 may include one or more processing cores with each core configured to perform independently. A multi-core processor enables multiprocessing within a single physical package. Examples of a multi-core processor include two, four, eight, or greater numbers of processing cores. Alternatively, or in addition, the processor 204 may include one or more microprocessors configured in tandem via the bus 202 to enable independent execution of instructions, pipelining, and multithreading. The processor 204 may also be accompanied with one or more specialized components to perform certain processing functions and tasks such as one or more digital signal processors (DSP), and / or one or more application-specific integrated circuits (ASIC). Other specialized components to aid in performing the inventive functions described herein include one or more field programmable gate arrays (FPGA) (not shown), one or more controllers (not shown), or one or more other special-purpose computer chips. The system 200 may further include an interface 208, such as a communication interface (with the said terms being interchangeably used) which may enable the test suite management system 200 to communicate with other systems for receiving and transmitting information. The communication interface 208 may include a medium (e.g., a communication channel) through which the system 200 communicates with other system. Examples of the communication interface 208 may include, but are not limited to, a communication channel in a computer cluster, a Local Area Communication channel (LAN), a cellular communication channel, a wireless sensor communication channel (WSN), a cloud communication channel, a Metropolitan Area Communication channel (MAN), and / or the Internet. Optionally, the communication interface 208 may include one or more of a wired connection, a wireless network, cellular networks such as 2G, 3G, 4G, 5G mobile networks, and a Zigbee connection.

[0035] The system 200 also includes a template database 210. As used herein, the template database 210 is an organized collection of structured data, typically stored in a computer system and designed to be easily accessed, managed, and updated. The template database 210 may be in form of a central repository of information that can be queried, analysed, and processed to support various applications and business processes. In the system 200, the template database 210 provides mechanisms for storing, retrieving, updating, and deleting data, and typically includes features such as data validation, security, backup and recovery, and data modelling. The template database 210 stores multiple templates that are generated by the said process. Here, each template is mapped to multiple keywords which are generated automatically based on parameter name and user comments. The template database 210 keeps growing as a project engineering hub 406 matures over a period of time as new templates and personalized templates of users are stored in the template database 210.

[0036] The system 200 further includes an input device 212 and an output device 214. The input device 212 may take various forms depending on the specific application of the system 200. In an example, the input device 212 may include one or more of a keyboard, a mouse, a touchscreen display, a microphone, a camera, or any other hardware component that enables the user to interact with the system 200. It is to be understood that, when reference is made in the present disclosure to the term “display” this refers generically either to a display screen on its own or to the screen and an associated housing, drive circuitry and possibly a physical supporting structure, of which all, or part of is provided for displaying information. In the present system 200, the processor 204 and accompanying components have connectivity to the memory 206 via the bus 202. The memory 206 includes both dynamic memory (e.g., RAM, magnetic disk, writable optical disk, etc.) and static memory (e.g., ROM, CD-ROM, etc.) for storing executable instructions that when executed perform the method steps described herein for managing the testcases in the testsuite. In particular, the memory 206 includes a template management unit 216 to perform steps for managing the templates for the project engineering. Also, in the system 200, the memory 206 may be configured to store the data associated with or generated by the execution of the inventive steps.

[0037] Referring to FIGS 1 and 2 in combination, the various steps of the method 100 as described hereinafter may be executed in the system 200, or specifically in the processor 204 of the system 200, for managing the templates for the project engineering. For purposes of the present disclosure, managing the templates for the project engineering in the present method 100 is embodied as an suggestion algorithm for suggesting templates based on an adaptive questionnaire. It may be appreciated that although the method 100 is illustrated and described as a sequence of steps, it may be contemplated that various embodiments of the method 100 may be performed in any order or a combination and need not include all of the illustrated steps.

[0038] In embodiments of the present disclosure, at step 101 , the method 100 includes displaying a series of questions related to an industrial automation service associated with the project engineering. The questions are nested questions and are related to one another. The questions clarify user requirement for the template. For example, the user requirement may be to generate a template for commissioning a safety switches for a particular project. Then the questions can be associated with for example quality specifications such as the rate of manufacturing, size of the safety switches, quality tolerances, electrical specifications, actuators, etc. The series of questions are provided on a graphical user interfaces (GUI) that enable user to provide the input to the series of questions.

[0039] In embodiments of the present disclosure, at step 102, the method 100 includes receiving an input for a question of the series of questions. Each succeeding question in the series of questions is automatically adapted based on the input to the question using machine learning (ML) technique. The series of questions are generated based on the keywords associated with the project engineering using an artificial intelligence (Al) mechanism and / or a machine learning (ML) mechanism including Bayesian networks and decision tree. The questions are automatically adapted based on the input to the question by determining the plurality of keywords associated with the project engineering based on the input for the question and determining a first set of questions of the series questions is obsolete and a second set of questions is to be used to replace the first set of questions of the series of questions, based on the keywords. Further, replacing the first set of questions by the second set of questions and automatically adapting the series of questions by re-ordering the second set of questions of the series of questions based on an order. The order is determined based on a priority of the industrial automation service.

[0040] For example, questions can be “safety switches to be used as mechanical position switches or just position switches”? Based on the input to this question the next set of questions will be adapted i.e. , if the user inputs that they are looking for safety switches to be used as mechanical position switches then the questions related to the usage of the safety switches as mere position switches is dropped form the series of questions and adapted to the user requirement. As a result, the irrelevant questions are dropped, and the user has to answer only the questions which are relevant to their requirement.

[0041] In embodiments of the present disclosure, at step 103, the method 100 includes determining a keyword from the input and an objective associated with the project engineering. The input and the objective associated with the project engineering are parsed to obtain the keywords. Further, plurality of parameters and user comments associated with the project engineering are also parsed to obtain the keywords. For example, consider a project associated with sensing with position and safety switches. Then the parameters can be standard or safety application for positioning of the switches, design type, dimensions of the switches, special features of the switches, electrical specification, etc. The user comments can be for example, the comments or requirements received from project managers (PMs), comments by designers, vendor requirement, etc. The objective associated with the project engineering can be for example automating a customers’ auto-factory environment. Here the keywords can be “automate”, “factory”, “auto”, etc.

[0042] In embodiments of the present disclosure, at step 104, the method 100 includes determining a template from a template database 210 based on matching of the keyword and / or semantic labels which is determined form the input. The template includes specification for the project engineering, defining the industrial automation service to achieve at least one manufacturing goal. The template may also include for example but not limited to a set of user selectable options, a functional specification, a Piping and Instrumentation drawing (P&ID drawing), an electrical drawing, a design template, an operation, or a manufacturing execution system (MES). The functional specification may be for example a generic list of equipment required to achieve the described functionality.

[0043] In the template database 210 the various templates are stored such that they are linked to multiple keywords which are associated with that template. For example, template related to relays are linked to keywords such as for example, relay, switch, current, mechanically movable contact, spring, coil, contact, poles, latch, Buchholz, etc. Once the various keywords are obtained by parsing the parameters, the input, the user comments and the objective, the system 200 runs a search to determine same keywords in the template database 210. In another example, ML techniques with categorization models can be used for to find the best match between the keywords and / or semantic labels from the input and the template database 210. One method is based on direct keyword matching which is enhanced by categorization algorithms to rank questions according to the frequency of the used keywords.

[0044] On determining a match between the keywords from the inputs and the keywords linked to the templates in the template database 210, the template corresponding with the matched keyword is populated to the user. Here, it may be noted that though the explanation is provided with respect to a single template the keyword may match with multiple templates and the multiple templates are populated to the user. The user can then select the appropriate template from the list of multiple templates. Further, the template dataset 210 is explained in FIG. 3 of the description.

[0045] In embodiments of the present disclosure, at step 105, the method 100 includes generating the determined template in an exportable format based on user selection, for the project engineering. Here, once the user selects the appropriate template from the list of templates suggested then the template is generated in the exportable format so that it can be used in the parametrization software. Therefore, the proposed disclosure ensures that the user is quickly able to get the required template by answering a minimum number of questions with high efficiency. Since the template management unit 216 includes ML models which keep a track of the questions and adapt the questions based on the user’s response to a previous question, the proposed solution is highly adaptive and speeds up the process of obtaining the templates. Further, the method also includes receiving parameters for personalizing the determined template. Then generating a new template based on the personalization of the template and storing the new template in the template database 210. For example, if the user requires a type 1 motor to be run at speed X, then the template management unit 216 can obtain a template regarding running a type 1 motor, and modify the design pattern to operate the motor at speed X. As a result, the template database 210 is an ever-growing database which grows over a period of time.

[0046] Therefore, the proposed solution provides improved mechanism of template management for project engineering based on an adaptive questionnaire. In the existing solution, new projects are created from scratch or fresh using templates. The templates and wizards that aids in the project creation exists in some cases, but an assisted and personalized template suggestion with adaptive questionnaire provided by the proposed disclosure helps is optimizing the project engineering process. The method provided in the proposed disclosure reduces the project creation time in a big way and the manual parametrization in commissioning is drastically minimized. As a result, the proposed solution is simple and can be easily, effectively implemented with enhanced efficiency in the overall project engineering.

[0047] FIG 3 is an exemplary depiction of grouping of the templates in the template database 210, in accordance with one or more embodiments of the present disclosure. Referring to the FIG. 3, the template database 210 includes multiple combinations created programmatically. Each template in the template database 210 is assigned keywords. These keywords are used to generate meaningful questions and get user input using the Al based Reverse quizzing approach. The most relevant template is chosen from the template database 210 based on answers to the questionnaire. The questionnaire is adaptive based on learning with the objective of asking the user as Minimal number of questions as possible to arrive at the most suitable template from the template database 210.

[0048] The template database 210 includes templates and application examples. These templates are mapped with associated keywords generated automatically based on the parameter name and user comments. The template database 210 keeps growing as the hub matures. The decision trees are used to represent template data. The decision trees belong to a class of supervised machine learning algorithms, which are used here for classification of templates into clusters. The template is divided into multiple nodes depending on the grouping of variables in the template and each node has a separate decision tree. The Bayesian networks are also used in the template database 210 and is a form of Probabilistic Graphical Model used to build models from data and / or expert opinion. Here, the data is the keywords, and the expert opinion can be for example user comments on the requirements. The Bayesian networks are generally used for applications like diagnostics, reasoning, causal modelling, decision making under uncertainty, anomaly detection, automated insight, and prediction, etc. The Bayesian networks include multiple nodes. The nodes and links form the structure of the Bayesian network called a structural specification. The links are added between the nodes to indicate that one node directly influences the other. When a link does not exist between two nodes then such nodes may be connected via other nodes. They may however become dependent or independent depending on the evidence that is set on other nodes.

[0049] In another embodiment, the system 200 generates a list of templates relevant to the industrial automation service from the template database 210 based on the match. Here, each template in the list of templates is provided with a relevance score and the final relevant template is determined from the list of templates comprising the highest relevance score.

[0050] FIG 4 is an exemplary depiction of flow of the template generation based on an adaptive questionnaire, in accordance with one or more embodiments of the present disclosure. Referring to the FIG. 4, at step 402, the input provided is keywords generated from the automation objective into the project engineering hub 406. At step 404, the answers to the questions provided by the system 200 are provided as input to the project engineering hub 406. The project engineering hub 406 includes various machine learning models 408 and the template database 210. The templates in the template database 210 are mapped with associated keywords generated automatically based on the parameter name and user comments. The template database 210 keeps growing as the project engineering hub 406 matures. Therefore, the proposed solution provides the most appropriate template available for the user, that reduces manual effort considerably in the project engineering.

[0051] The questionnaires guide the commissioning process by posing relevant questions from studied patterns emerging from the firmware requirements, dependencies, and the violation of the domain constraints. As the questionnaire is answered, algorithm chooses the most appropriate template, the objective of the algorithm will be to ask minimal questions as possible to derive at the most appropriate template. For this objective, most im- portant parameters shall be identified from template and asked in early questions. For example, first question can be for identifying the purpose of the SIMOCODE project in natural language, upon decoding this a set of possible configurations from the available SIMOCODE project template database 210. Then major parameters of these configurations can be the questions to narrow in to most appropriate configuration .

[0052] FIG 5 is a flowchart representation of a method of generating the template based on the adaptive questionnaire, in accordance with one or more embodiments of the present disclosure. Referring to the FIG. 5, backend process of creating the template database 210 starts from step 502. At step 502, the method includes receiving existing templates and examples of applications associated with the industrial automation services. The templates can include the new templates generated by the users and templates personalized by the user. At step 504, the system 200 assigns keywords to the templates and the examples and stores the templates with the keywords assigned in the template database 210. The keywords are assigned to the templates based on the parsing agorithm. The comments and the key parameters identified by the algorithm can be the deciding inputs. The template database 210 is a growing database as the newly created templates by the user also gets added as the project engineering hub 406 is used.

[0053] Here the generation of the adaptive questionnaire and the template recommendation is provided. At step 506, the adaptive questionnaire is genreated using AI / ML techniques including the Bayesian networks and the decision tree. The generated adaptive questionnaire is then displayed to the user, where the user selects answers to the questions displayed on the screen. The questionnaire is adaptive because as and when the user selects the answer to a first question the system 200 automatically learns the user’s answer and the context thereby using the same to generate and pose relevant questions based on the user’s answer to the first question.

[0054] At step 508 the system 200 parses the user’s response to the adaptive questionnaire and determines whether any matching template is available in the template database 210, which suits the user’s requirement based on the user’s response. At step 510, the system 200 retrieves the matching template on determining the matching template is available in the template database 210. At step 512, the system 200 allows the user to personalize the retrieved template based on user requirement. At step 514, the personalized template is saved as a new template in the template database 210 and the relevant keywords are mapped to the new template. Further, at step 516, the new template is exported in a downloadable format to be used in the parametrization software.

[0055] The proposed disclosure retrieves the matching template from the template database 210 by asking as minimal questions as possible which is most appropriate based on the user’s response to the questions. The adaptive nature of the questions based on the user’s response ensures that different types of users are handled differently. For example, a new user may not be aware about the different requirements for the template and may need to answer a large number of questions. However, a seasoned user may know the exact requirement for the template and may not be required to answer the same number of questions that are posed to the new user. At times answering a large number of questions may be cumbersome and irritating for the seasoned users. The proposed disclosure addresses such scenario by continuously adapting the questions to be answered by the user based on the user’s response to the answered questions.

[0056] FIG 6A-6D are exemplary depiction of graphical user interfaces (GUIs) leading to generation of a personalized template, in accordance with one or more embodiments of the present disclosure.

[0057] Referring to the FIG. 6A, a GUI of the system 200 is provided where the user is presented with a landing page. Here the user can choose to either search for the template themselves using keywords or can take assistance from the system 200 for the same. The proposed soliton is more valid when the user takes assistance from the system 200 to suggest the appropriate template.

[0058] FIG. 6B provides details of the questions displayed on the left-hand side of the screen of the system 200 which includes device type, version number, etc. Here, as and when the user selects the input to the questions the system 200 automatically determines the matching templates and populates them on the right-hand side of the screen. Here, it may be noted that the process of determining the matching template happens very quickly resulting in close templates being populated simultaneously. As and when the user answers questions which are intelligently adapted based on the users answers to the previous question, the list of templates may reduce zeroing on the most relevant template.

[0059] Consider that in the FIG. 6B, the user selects the template “Configuration Beta”. In the FIG. 6C, the system 200 provides an option to the user to personalize the selected template based on the user requirements. FIG. 6D indicates that the user provides the personalization parameters and export the personalized template in an exportable format. It may also be noted that the personalized template is saved to the template database 210 for further use. Therefore, when the user needs the same configuration which is personalized then then user can directly use the saved template from the template database 210.

[0060] While the present disclosure has been described in detail with reference to certain embodiments, it should be appreciated that the present disclosure is not limited to those embodiments. In view of the present disclosure, many modifications and variations would be pre- sent themselves, to those skilled in the art without departing from the scope of the various embodiments of the present disclosure, as described herein. The scope of the present disclosure is, therefore, indicated by the following claims rather than by the foregoing description. All changes, modifications, and variations coming within the meaning and range of equivalency of the claims are to be considered within their scope.

[0061] Reference Numerals method 100 step 101 step 102 step 103 step 104 step 105 system 200 bus 202 processor 204 memory 206 interface 208 template database 210 input device 212 output device 214 template management unit 216 step 402 step 404 step 406 step 408 step 410 step 412 step 502 step 504 step 506 step 508 step 510 step 512 step 514 step 516

Claims

PATENTANSPRUCHE / PATENT CLAIMS1. A method for managing templates for project engineering, the method comprising: displaying a series of questions related to at least one industrial automation service associated with the project engineering; receiving an input from a user, for at least one question of the series of questions, wherein each succeeding question in the series of questions is automatically adapted based on the input to the at least one question; determining at least one keyword from the input and an objective associated with the project engineering; determining at least one template from a template database (210) based on a matching of the at least one keyword; and generating the at least one determined template in an exportable format based on user selection, for the project engineering.

2. The method (100) according to claim 1 , further comprising: receiving at least one parameter from the user for personalizing the determined template; generating a new template based on the personalization of the determined template; and storing the new template in the template database (210).

3. The method (100) according to claim 1 , wherein the template comprises specification for the project engineering defining the at least one industrial automation service to achieve at least one manufacturing goal.

4. The method (100) according to claim 1 , wherein the template database (210) comprises a plurality of templates and wherein each template of the plurality of templates is mapped to a plurality of keywords.

5. The method (100) according to claim 1 , wherein each template of the plurality of templates is mapped to the plurality of keywords based on parsing of a plurality of parameters and user comments associated with the project engineering.

6. The method (100) according to claim 5, wherein each template of the plurality of templates are classified into clusters using decision trees.

7. The method (100) according to claim 1 , wherein determining the at least one template from the template database (210) based on the matching of the at least one keyword comprises: matching the determined at least one keywords and semantic labels associated with the input with the keywords and semantic labels in the template database (210); generating a list of templates relevant to the industrial automation service from the template database (210), based on the matching the keyword and semantic labels associated with the input with the keywords and semantic labels in the template database (210), wherein each template in the list of templates is provided with a relevance score; and determining the at least one template from the list of templates comprising the highest relevance score.

8. The method (100) according to claim 1 , wherein each succeeding question in the series of questions is automatically adapted based on the input to the at least one question by: determining the plurality of keywords associated with the project engineering based on the input for at least one question; determining a first set of questions of the series of questions is obsolete and a second set of questions is to be used to replace the first set of questions of the series of questions, based on the keywords; replacing the first set of questions by the second set of questions; and automatically adapting the series of questions by re-ordering the second set of questions of the series of questions based on an order.

9. The method (100) according to claim 1 , wherein the series of questions are generated based on the plurality of keywords associated with the project engineering using at least one of an artificial intelligence (Al) mechanism and a machine learning (ML) mechanism.

10. The method (100) according to claim 7, wherein the order is determined based on a priority of the at least one industrial automation service.

11. The method (100) according to claim 1 , wherein the series of questions are provided on a graphical user interfaces (GUI) that enable user to provide the input to the series of questions.

12. A system (200) for managing templates for project engineering, the system (200) comprising: an interface configured to display a series of questions related to at least one industrial automation service associated with the project engineering; a processor (204); and a memory (206) coupled to the processor (204), wherein the memory (206) comprises instructions which, when executed by the processor (204), configures the processor (204) to: receive an input for at least one question of the series of questions, wherein each succeeding question in the series of questions is automatically adapted based on the input to the at least one question using machine learning (ML) technique; determine at least one keyword from the input and an objective associated with the project engineering; determine at least one template from a template database (210) based on a matching of the at least one keyword; and generate the at least one template in an exportable format based on user selection, for the project engineering.

13. A computer program product, comprising computer program code which, when executed by a processor (204), cause the processor (204) to carry out the method (100) of one of the claims 1 to 11.

14. A computer-readable medium comprising a computer program product comprising computer program code which, when executed by a processor (204), cause the processor (204) to carry out the method (100) of one of the claims 1 to 11.

Images