Web-enabled platform for distributed and dynamic ... - Springer Link

Int J Adv Manuf Technol (2008) 38:1260–1270 DOI 10.1007/s00170-007-1172-z

ORIGINAL ARTICLE

Web-enabled platform for distributed and dynamic decision-making systems Ahad Ali & Zaifeng Chen & Jay Lee

Received: 18 March 2007 / Accepted: 18 July 2007 / Published online: 22 August 2007 # Springer-Verlag London Limited 2007

Abstract With the advent of internet and wireless technologies, real-time remote monitoring and control is becoming an essential need for meeting highly dynamic business objectives. At the same time, web-enabled platforms are required to perform remote monitoring with efficiently and effectively. Recent progresses on e-manufacturing applications address the needs for better integration between factory floor and enterprise systems. This paper presents a web-enabled platform which focuses on web-enabled intelligence to enable products and systems to achieve near-zerodowntime performance through device-to-business (D2B) platform. The proposed web-enabled platform can effectively minimize the massive information bottleneck that exists between plant floor and information systems. Case studies are presented to determine how effectively web-enabled industrial system can be used in factory floor as well as business decision-making. Manufacturers and users will benefit from the increased equipment and process performance with the effective implementation of the developed web-enable platform. Keywords Device to business . Internet-based systems . Remote monitoring . Web-enabled systems A. Ali (*) Industrial Engineering, University of Puerto Rico-Mayaguez, 250 N. Post Street, Mayaguez, PR 00681, USA e-mail: [email protected] Z. Chen Automated Precision, Inc., Rockville, MD, USA J. Lee University of Cincinnati, Cincinnati, OH, USA

1 Introduction There is a growing demand to connect front-end business with backend business to synchronize the manufacturing systems and product services and customer relationship. The trend of the future e-business is to bridge the gap between front-end and backend business. Web-enabled platform will bridge the gap and become a common platform for e-business and emanufacturing systems to effectively minimize the massive information bottleneck between plant floor and information systems [1]. Next-generation smart manufacturing companies necessitate a set of core intelligence for addressing the smart business performance: called “5Ps,” namely predictability, producability, productivity, pollution prevention, and performance. These core intelligences may help to develop a series of well-established prediction and optimization business methods which provide us with scientific understanding about manufacturing business and enable us to focus on design, manufacture, and deliver customer’s solutions and select the optimum course of action for service innovation for life cycle support of the product [2]. To get maximum performances from the assets (equipment, products, process, etc.), webenabled systems with intelligence can be used to monitor, analyze, compare, and sustain the system via internet. Rockwell Automation stated four competencies: design, operate, maintain and synchronize for any manufacturer to be a world class manufacturing company [3]. e-Manufacturing is a transformation system that enables the manufacturing operations to achieve predictive near-zero-downtime performance as well as to synchronize with the business systems through the use of web-enabled and tether-free (i.e., wireless, web, etc.) infotronics technologies. It integrated information and decision-making among data flow (machine/process level), information flow (factory and supply system level), and cash flow (business system level) [4, 5].

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Int J Adv Manuf Technol (2008) 38:1260–1270

Currently, the industry is pushing toward web monitoring of the facilities through software and internet. A set of software technologies is developed to help build, deploy, operate, integrate, aggregate, and consume a spectrum of services delivered over the web [6]. These new technologies allow the user to access plant data through an Internet browser, but the access is mostly passive and lacks the capability to perform any control or configuration tasks on the machines themselves. Pasek et al. developed a webenabled monitoring and control of manufacturing systems which relies on Internet technologies (including client/ server architecture, web browsers and databases) and platform-independent software (including object-oriented programming, Java language, etc.) [7]. Qu et al. addressed various issues related to design and deployment of a webenabled distributed control application platform for industrial automation where the built-in web functions enable programming and execution of remote control applications through a web browser [8]. A real-time web-based machine tool and machining process monitoring system is developed as the first step for implementing e-manufacturing system. The current variations of the main spindle and feeding motors are measured using hall sensors. A rule-based expert system is applied in order to decide the machining process and machine tool are in normal conditions. Lee [9] discusses how to design smart products and service systems using web-based intelligence technologies and its impacts on innovative business transformation. Djurdjanovic et al. [10] presented web-enabled remote technology and prognostic methods to enable a “zero” distance between the customers and equipment makers and “near-zero” downtime performance and provide possibility of delivering justin-time service. Li et al. [11] presented an agent-based platform for web-enabled equipment predictive maintenance system. They have analyzed the structure of webenabled predictive maintenance system for single machine and extended to the factory level with many different equipments and the enterprise level for global production. Yao [12] developed a web-based remote control platform using digital cameras, a programmable logic controller (PLC) and a PC-based visual basic human-machine interface (HMI) to create a flexible manufacturing system (FMS). An FMS can be easily controlled and monitored through an Internet-based PLC-control system using a PCbased HMI platform. From remote locations, this platform enables management to effectively monitor, control and diagnose a manufacturing process via the Internet. Lee et al. [13] introduces the emerging field of e-maintenance and its critical elements. Performance assessment and prediction tools are introduced for continuous assessment and prediction of a particular product’s performance, ultimately enable proactive maintenance to prevent machine from breakdowns. Recent trend of information technology, web-based

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manufacturing systems are expected to meet the need of many manufacturing industries to adopt e-manufacturing system for globalization, agility, and digitalization to cope with the rapid changing market requirements [14]. The existing systems have significantly lagging to integrate shop floor information with upper level management decision. Many companies are struggling with vertical integration due to the level of information sharing. Horizontal integration might provide better information integration between lower level operations and upper level management decisions. However, it might not be applicable in all scenarios. Therefore, companies are looking toward how to integrate factory floor operations with decision support systems. Manufacturing companies are getting distributed due to outsourcing and market competition. It gets more complex in the distributed manufacturing systems. The proposed web-enable provides a better platform to minimize the information gap between those levels of information. The web-enabled platform and intelligence are not well developed to bridge the gap between factory floor and e-business for real-time decision-making. The proposed web-enabled D2B system brings the manufacturers in a position where they can easily look through their real-time factory floor information and gives capability with agility to respond quickly for changing production environment. It gives the flexibility and visibility to the production process.

2 Web-enabled systems Web-enabled system is the fastest and easiest way to bring your real-time data onto the World Wide Web. It is a stateof-the-art component-based software product for factory floor data, which provide real-time data from a factory floor line into a database ultimately directly onto the web. Webenabled D2B platform is an integrated, visual environment that supports real-time web-based information systems and allows flexible web-enabled monitoring and analyzing. The web-enabled applications provide a web browser as a graphical user interface (GUI) enabling a thin-client application architecture. Generally, the proposed approach requires three basic components: a client web browser that serves as a user interface, network connection and HTTP (hypertext transfer protocol) server to publish the required information using XML (eXtensible markup language), HTML (hypertext markup language), etc. The content of a web site is stored in a set of web pages, which are dynamically updated to synchronize their content with the real-time data provided by an application server. The web platform provides considerable advantages over traditional client/server applications. Web-enabled remote monitoring device interface and system technologies need to be

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developed based on generic equipment model (GEM). The major purpose is to minimize the need for a struggle with distributed application development and deployment issues and to allow industry engineers to focus on application functionality instead. The technical architecture of the webenabled platform is shown in Fig. 1. The platform is an integrated platform to develop building applications and create sophisticated web-based applications. It contains all the information related to monitoring which are, (a) the number of machines, devices and installation, (b) data server, (c) application server, (d) web server, and (e) web-browsers. All the data collected from the devices and machines will be stored in databases, which can be integrated with enterprise resource planning systems. Moreover, the web browser can be linked with supply chain management. Under this architecture, the application server is a process that communicates with the real-time data server to access data from the factory floor or from a database. The data are processed and packaged in suitable formats, i.e., XML for further visualization on the web or storing into a database. The application server may be interfaced with any relational database through a common protocol. The overall system architecture is inherently distributed; i.e., the real-time data server, the application server, and the web server may be physically deployed either on a single PC or on networked computers. Each web page distributed by the web server contains formatted HTML text and several applets that periodically request data from the web server. Upon the first client request a web server creates and initializes a servlet that allows access to the application server. Every time a client requests data from the web server, it delegates the request to a corresponding servlet that in its turn requests appropriate data from the application server. Once retrieved, data are distributed to the client that requested them. The platform uses GEM@Work to implement web-enabled concept and also added intelligence to the systems for web-enabled Web Browser

Web Browser

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Fig. 1 Technical architecture of web-enabled platform

Factory Floor/ Equipment

monitoring system out of product and equipment components [15]. The proposed web monitoring architecture includes bringing about innovations on intelligent machine assessment methodologies, information integration between factory floor and business systems as well as to develop advanced maintenance and service technologies to enable manufacturers and customers to sustain their assets with minimum downtime conditions.

3 Device-to-business (D2B) platform and methodologies Device-to-Business (D2B) is an intelligent tool that enables a product or a system to directly link to a business decision making devices or systems. It also provides a solid framework for intelligent prediction agents. For example, a machine tool can monitor its tool wear and order its worn tools from the tool vendor or allow for troubleshooting remotely. A copy machine can monitor its performance and requests service before a failure occurs. The ultimate goal is to enable a product to order its own parts or call for automated services to achieve near-zero-downtime performance through the D2B platform. According to the white paper on making sense of emanufacturing by Rockwell automation, one of the four enablers of e-manufacture is asset management and reliability-centered maintenance-tools, methodologies, and services for increasing overall asset utilization with minimizing unplanned maintenance and unexpected downtime. D2B platform provides the viable solutions to this challenge. Moreover, D2B platform aims to be a “bridge” between the e-manufacture and e-business systems. The developed D2B consists of the following elements and functionalities (a) Data acquisition: it allows a direct interface with any data acquisition systems to obtain real data is definitely the first step. Data can come from sensor or other device, like computer numerical control (CNC) controller. (b) Data distribution: to make data available to applications is the only way to make sense of those data. Additionally, data security is also our concern. (c) Data mining: data have to be transferred into information somehow by data analysis applications. Degradation watchdog agent can process the data from equipments, estimates their status and degradation index that are useful information for maintenance. (d) Information distribution and utilization: information has value only when it can be used to reduce cost or to boost revenue. For example, machine degradation index can be used by schedule optimization application to reduce total cost. The more applications make use of


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adapter, etc. this layer called the interface layer, does the signal processing which is called data transformation layer, after the sugnal processing, it is required to transfer data into intelligent information, this requires data trnasfer layer and ultimately the intelligent tools provides prediction, andalysis and benchmarking. After getting the intelligent information, optimization and sysnchronization with eBusiness systems needs to be done. The sysnchronization module will provide interface using intranet/internet to connect with supply chain management (SCM), customer relation management (CRM) and enterprise resource planning (ERP). The detail information flow inside D2B is shown in Fig. 3.

the information, the higher the value of the information can be. Information security is important too. (e) Alien system friendly: in the complexity of the world, D2B platform cannot solve all problems. Instead, D2B platform provides friendly interface to synchronize with e-business system.

3.1 Architecture of device-to-business (D2B) platform D2B platform architecture is depicted in Fig. 2. All rectangles (prediction, synchronization, signal processing, etc.) stand for reusable components of D2B platform. It is an open architecture that is friendly to alien systems. The importance of synchronization between factory floor and ebusiness leads to develop D2B platform which is designed for intelligent prediction, diagnostics and synchronize with realistic decision-making systems to minimize downtime as well as reduce uncertainties. Initially the raw data is stored in local SQL database, and it does the preprocessing of the data before sending it into central database. It reduces the massive raw data flow from factory floor, only required critical information is sent to the distributed systems. As the raw data comes from different methods with different characteristics, it is required to control the data and information flow instead of simple store data. Existing systems are lagging behind to provide these types of information integration with factory floor and business system. D2B platform provides the intergration between the factory floor and e-business system. Initally the sensors, controller and operator with data acqusion using their free systems including intranet/internet. This layer is called the communication layer. To get the data, using human machine interface (HMI), data acquision (DAQ) and Fig. 2 Architecture of deviceto-business

4 Synchronization and integration of D2B using web services Synchronization between factory floor system and ebusiness system are significant for real-time decision making in-terms of near-zero downtime, reducing uncertainties, and improved system performances. For instance, by knowing the degradation of machines in the production floor, the operation supervisor can estimate its impacts to the materials flow and synchronize it with the ERP system. The revised inventory needs and materials delivery can also be synchronized with other business tools such as CRM system. Moreover, suppose a cutting tool wears out, the information can be directly channeled to the tool suppliers, and also update the database for tool performance management. In this case, cutting tool companies no longer sell cutting tools, but instead, sell cutting time. In addition, when the machine degrades, the system can initiate a service call through the service center for prognostics. However, there exist several challenges listed below

SCM SCM

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Fig. 3 Data flow inside D2B

regarding the smoothness of synchronization and business automation. –

–

Data from various machinery, devices and processes must be processed (analyzed) and be sent to disparate e-business systems. Advanced prediction methods and tools need to be developed in order to detect degradation, performance loss or trend of failure not faults, breakdowns, etc.

Web service is called the next generation of distributed computing. It is defined by several technologies including simple object access protocol (SOAP), web services description language (WSDL) and universal description, discovery, and integration (UDDI). SOAP defines a model for exchanging XML information, WSDL is a language for describing service, and UDDI is a directory for finding services available. Together they enable a new model for web-enabled applications for reusable components supported on the web [16]. With web services, any application can be integrated as long as it is Internet-enabled. The foundation of web services is XML messaging over standard web protocols such as HTTP. With web services, integrating separate businesses, departments, or applications can be quick and cost-effective. By importing the system, the state of machines can be monitored in real-time. A watchdog agent is employed to diagnoses the machine and to estimate how good the machine is and when the maintenance will be required. When some maintenance activities are scheduled, the new schedule can be simulate to estimate whether it will cause the production to be over due and optimization software can be called to look for a better schedule. In the based web service systems, an on-site computer or embedded system collects data from equipments by A/D or other methods. Then the data is enveloped into SOAP package and is sent to the web service server. The transport between the on-site computer and server can be HTTP,

simple mail transfer protocol (SMTP), etc. HTTP transport is chosen in this case. The web service server can be any server that understands SOAP standard. HTTP servelet (java servelet), server side scripts (.net asp) or embedded HTTP server may be used. After web services server receives a request from the on-site computer, it has the freedom of how to utilize the data. The data can be stored in the database or be processed for diagnosis and prognostics. This system structure is highly scalable. For example, the data is being stored into a database. For a small company, the database system can be access database. For middle size companies, the database system can be structured query language (SQL) server on Windows 2000 server. For big companies, the database system can be Oracle on UNIX box. However, only one kind of web service client is required. Even though the system has to be upgraded for fast changing technology, the clients do not have to be changed, which reduce the pain of growth. In the first scenario, all data is sent to the server where an intelligent prediction agent can reside. It might not be a good idea because too much data is thrown into the network and most traffic is useless. A better solution should be that raw data be processed locally and only useful information will flow on the network. In the second scenario an intelligent prediction agent is resident in the machine. Raw data is processed locally. The service request will be sent to the web service server only if the intelligent prediction agent finds something wrong. For example, the intelligent prediction agent processes raw data and draw a conclusion that a part is going to fail. So it sends this information to the server. In the server side, a period maintenance for this part has been schedule. In order to avoid that the part really fails before the period maintenance, the intelligent prediction agent is informed by response from the server that it should send out emergent request to the server again if the confidence index of the degradation of that part increases from 60% to 85%.

Int J Adv Manuf Technol (2008) 38:1260–1270 Fig. 4 D2B platform based on web service system

Machinery

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Signal

Request:

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Parameter Matrix

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34.67 ... ...

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Owning to the local intelligent prediction agent, the traffic on the network is dramatically reduced. Usually, the intelligent prediction agent has a fixed logic structure but the parameters of the logic have to be generated from a set of typical failures of specific machine. However, it is impossible to cover all possibilities in the real world. The code to handle such exception in intelligent prediction agent is the hardest part. The third scenario is suggested to solve the problem which is shown in Fig. 4. In the third scenario, the local intelligent prediction agent sends a request to the server while an exception is detected. After the server receives the exception service request, there are several options for the server. If such an exception has been included into the server database and a new set of parameter matrix is ready, just return the new parameters and update the local intelligent prediction agent parameter matrix. If the exception is a new one and the server does not have the answer ready for that, the server can generate a special request to specialists and ask the local intelligent prediction agent to poll the answer later. Specialists may be contacted or some expert system will be activated to obtain an answer automatically. After the deliberation, the service servers can respond for the “exception” request with the modified watchdog logic parameter matrix. The three scenarios can be deployed step by step. The first scenario is the simplest one and can be deployed first. Raw data will be directly sent to the server side, so the intelligent prediction agent can be tested in lab. When the watchdog logic is ready, the second scenario and the third scenario will be rolling next. In the diagrams for the three

scenarios, only device level of D2B is touched. In the system level of D2B shown in Fig. 5, the system structure is similar. The web service provider in the device level becomes service consumer in the system level (see system diagram). In the system level, some service providers are service consumers too. Since some existing systems do not support web service, it is important to integrate the old system into the system framework over web service. In such a case, a simple wrapper has to be written. For example, GEM@Work can be imported into the new framework by adding some web services beans. After industry object [15] is imported into the web services framework, industry object can work with more equipments and no longer is limited to those equipments supporting SEMI standard. In another example, Siebel system [17] can synchronize with D2B platform

Device level Web Service Provider

Request for scheduling maintenance

Request for optimization

System level

Schedule Service Provider

Optimization Service Provider

Request for simulation

Request for simulation

Simulation Service Provider Other Service ...

Fig. 5 Device level and system level diagram of D2B platform

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over web service by the aid of a middleware-Questra [18], which has be tested in the test bed (Fig. 6). For the products of Allen-Brady/Rockwell automation [19], it is a good idea to make a wrapper to connect Rockwell automation’s system and the platform over web services, with RSLinx OPC (OLE for process control) of Rockwell automation and Microsoft .net Visual Studio. Comparing to other distributed computation protocol, like common object request broker architecture (CORBA), component object model (COM), and remote method invocation (RMI), web service is better for loose coupling system though the efficiency of web service is lower. It might be proper to employ CORBA, COM or RMI for distributed computation inside same intranet and to employ the web service to connect each Intranet. Depending on the web service, manifold application can be synchronized and work together with less pain. On the other hand, web service, which will become a standard of W3c in the near future, is supported by the leaders of IT industry, like IBM, Microsoft, SUN and so on. A lot of state-of-art developing software, including Microsoft .net, SUN J2EE, Borland Delphi 6, IBM WebSphear and Questra A2B platform, make the developing of web service fairly smooth. It can be concluded that the D2B infrastructure over web service is a solid platform with outstanding flexibility.

5 Case study on web-enabled systems 5.1 Case study: medical equipment test cell In today’s increasingly competitive business environment, organizations are finding themselves more concerned than ever with retaining customers through better quality, on time delivery, flexibility and cost reduction. Therefore, a solid business strategy is necessary for survival in today’s business world. This requires real-time information management tool, continuous improvement, and monitoring for factory process. The case study will illuminate the utilization of the web to perform, monitoring, analysis and prediction on the medical equipment test cell. The study provides a platform for the following: (a) define, design and develop a system for real-time remote monitoring, (b) signature analysis of system data over web, (c) online and real-time system control from remote location, and (d)

SIEBEL Services request

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Services request over web service

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Database ODBC driver

Outlook application

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Cell phone: Alert

Fig. 7 Software flow chart for web display and alert generator

automatic notification massages (phone, e-mail, and pager) [20]. The target was to demonstrate the feasibility of D2B platform. The scope of the case study is the utilization of a web-enabled system and applications for monitoring of medical equipment test cell. The case study addresses the followings: (a) no interference with existing protocols, products or manufacturing processes, (b) identification of appropriate system breakdown and degradation events, (c) design and implement an interface to communicate with the data (events), (d) implement real-time alert triggering mechanism, (e) design and implement web pages to monitor and control data (events), (f) evaluate and display signature of the process, and (g) integrate and test the above components in real application and lab environment. Medical system tubes business makes a computer tomography (CT) system for reviewing human muscles tissues and internal organs. The tube (X-ray emitter) generates X-rays, which helps doctors and/or appropriate medical personnel to diagnose irregularities of the patient. The last step in the tube making process is the functional test cell. This system runs the same protocols at CT Gantry

Company website

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Fig. 6 Synchronization with web service

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Fig. 8 Overall architecture of the web enabled platform for medical equipment test cell


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Fig. 9 Current and historical test information

before the X-tube is shipped to a hospital for replacement of a failed tube or CT manufacturing. The primary criticalto-quality (CTQ) defect is called SPITS. A spit is a voltage spike, which occurs during the generation of X-rays. Each spit causes an aberration on the CT image. This is dangerous because a doctor can mis-diagnose patient based on this flat image. This can be very costly to the doctor and Fig. 10 Functional test SPITS monitoring

even deadly to the patient. It is imperative that tubes have minimal spit counts when passing the last step in the functional test process. The test lasts approximately two hours as the tube rotor is ramped up and down between 1000 and 10,000 RPM. The process runs at accelerated rates to eliminate and or forecast potential defective (high “spit” count) tubes.

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Fig. 11 Lathe monitoring remote location (Michigan)

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Service Request Email, Call, Page, Alarm

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industrial objects. Then it linked with the web server to publish in the Internet. The current and history information of the pass fail and reason details in web-enabled system is shown in Fig. 9 and the SPITS variation along the time is shown in Fig. 10. At a certain point, it is shown that the SPITS has crossed the limit and send messages for failure to take necessary actions.

Gearbox

When the functional test cell fails, it generates a message, which is stored in the database and the followings happen: (a) watch for alert events and send out messages to pager/email, (b) a lightweight application written in C++ and (c) run as a low priority demon in the background. Several instances can run simultaneously. The software flowchart for alert generator depicts in Fig. 7. It uses Microsoft COM interfaces provided for MS Outlook and ActiveX data objects (ADO). After testing, it is found, that it works well in WinNT/2000 and is very efficient and cost effective. The following features can be added: multiple pager/email id feature; sophisticated selection of alert event, and can be developed further for remote web monitoring. The web-enabled architecture for the monitoring system is shown in Fig. 8 where the data is collected from functional test cell and then stored is database systems (MS access) using the on-board-computer (OBC). Then we developed the graphical user interface for web monitoring using

5.2 Case study: in-house gearbox and remote lathe The gearbox setup was oriented to present D2B using the products from the center’s member companies, this methodology is to transform data from devices or machines to networked user systems using XML, HTML, and SQL through the developed D2B platform for e-manufacturing implementation, this is because e-manufacturing cannot happen until the machines in factory level become webenabled. The scenarios of Figs. 11 and 12 are examples of

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Fig. 12 In-house gearbox monitoring system

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Fig. 13 Lathe performance monitoring remote location (Michigan)

using the platform as a transfer function between the manufacturing data acquisition system and business action server, correlating data from different formats and transforming them to a web-deployable system, and these data can be gathered from traditional control I/O or through a separate wireless data acquisition systems using different communication protocols. Fig. 14 In-house gearbox performance monitoring

The web-enabled platform provides a universal web browser client to monitor the gearbox performance measurement in real-time. It uses the application server to process real-time data from the SQL database where all gearbox data are stored. The data are packaged for visualization on the web. A remote monitoring testbed for lathe machine was setup at Michigan and sensors were used

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to collect information. The proposed web-enabled system monitors the performance of remote lathe machine using web services from Milwaukee. The temperatures of spindle, horizontal slide, vertical slide, and lathe table are measured and compared which are shown in Fig. 13. The variations of those temperatures could be easily recognized and analyzed remotely. Performance measurements for the inhouse gearbox are performed for temperature, current, and vibration. The real-time comparison between two sets of gearboxes is shown in Fig. 14. It shows regular performance and failure performances. Two case studies on medical equipment test cell and inhouse gear box have shown how effectively D2B platform for performance monitoring can be used and distributed. Since we are using web services for online monitoring, it will provide real-time information from the distributed system. Decision makers could easily use it to for their decision making. The platform could be integrated with other business platforms such as ERP, SCM etc. so that integrated decision-making will be more convenient and realistic. From the above case studies, we could conclude that real-life applications could use this web-enabled platform for real-time distributed decision-making. It has been recognized that massive information bottleneck exists between the plant floor and information management systems. In the web-enabled platform, the data is gathered locally and only critical information is transferred for web-based monitoring and integration. This will provide opportunity to minimize the information gap between factory floor and decision-making systems. Since, only critical information will be shared with the central server by filtration, the data traffic will be less. Moreover, there will be more effective decision making by including realistic information from remote location through web services.

6 Conclusions The web-enabled device-to-business (D2B) platform is to bridge the gap between factory floor and e-business systems using innovative web intelligence by monitoring and analyzing to enable manufacturers and customers to sustain their assets with near-zero down time conditions. This research provides architecture of device-to-business and proposes its elements and impact to achieve near-zero breakdown of products and systems through the advancement in web-enabled intelligence. It provides a systematic body approach in intelligent e-manufacturing systems for emaintenance systems in respect of next-generation products and service systems for assets management. As the system is still being developed, significant improvements with real


applications are needed to develop a robust system. Ultimately the proposed web-enabled platform can help manufacturers with real-time distributed decision-making.

References 1. Ali SA, Chen Z, Lee J, Koc M (2002) Intelligent web-enabled platform for tether-free monitoring systems. Institute of Industrial Engineering Research Conference, Orlando, FL, 19-22 May 2. Lee J (1998) Teleservice engineering in manufacturing: challenges and opportunities. Int J Mach Tools Manuf 38:901–910 3. Rockwell Automation e-Manufacturing Industry Road Map, http://www.rockwellautomation.com 4. Lee J, Ali SA, Koc M (2001) e-Manufacturing- its elements and impact, proceedings of the annual Institute of Industrial Engineering Research Conference Conference, 21-23 May, Dallas, TX 5. Koc M, Lee J (2001) A system framework for next-generation e-maintenance system. EcoDesign 2001, Second International Symposium on Environmentally Conscious Design and Inverse Manufacturing, 11-15 December 2001, Tokyo Big Sight, Tokyo, Japan 6. Allan G (2001) Casting a Wide.NET for Productivity, edirections, Winter 2001, 32, pp. 6–9 7. Pasek ZJ, Min BK, Marker S, Husted F (2001) Web-enabled monitoring and control of manufacturing systems. AC ’01 6th International Conference on Monitoring & Supervision in Manufacturing Warsaw, Poland, 27-28 August 8. Qu RT, Lim R, He H, Ding ZQ, Aendenroomer A, Goh KM (2003) A web-enabled distributed control application platform for industrial automation. Proc Emerging Technologies and Factory Automation, IEEE Conference, 16–19 Sept 2:129–132 9. Lee J (2003) Smart products and service systems for e-business transformation. Int J Technol Manag 26(1):45–52 10. Djurdjanovic D, J Yan, Qiu H, Lee J, Ni J (2003) Web-enabled remote spindle monitoring and prognostics. CIRP 2nd International Conference on Reconfigurable Manufacturing, Ann Arbor, MI. 20-21 August 2003 11. Li Y, Chun L, Ching ANY (2005) An agent-based platform for web-enabled equipment predictive maintenance. Proc IEEE/WIC/ ACM International Conference on Intelligent Agent Technology, IEEE Computer Society, Washington DC, USA, 00:132–135 12. Yao AWL (2005) Design and implementation of web-based diagnosis and management system for an FMS. Int J Adv Manuf Technol 26(11–12):1379–1387 13. Lee J, Ni J, Djurdjanovic D, Qiu H, Liao H (2006) Intelligent prognostics tools and e-maintenance. Comput Ind 57(6):476–489 14. Bong S, Gun K, Jin C, Byung J, Honghee L, Myeong C, Jin H, Dong P (2006) A web-based machining process monitoring system for e-manufacturing implementation. J Zhejiang University-Science A 7(9):1467–1473 15. GEM@Work & Siplace Explorer, Industrial Objects Inc 16. Web services overview, IBM, WSTK v2.42 17. Siebel Call Center, Siebel Inc 18. Questra A2B (Appliance to Business) systems 19. Rockwell Automation, http://www.rockwellautomation.com 20. Ali SA, Chen Z, Lee J, Koc M (2002) Web-enabled device-tobusiness (D2B™) Platform for distributed and dynamic decision making systems, Proceeding of the 5th International Conference on managing innovations in manufacturing, Milwaukee, WI, 9-11 September, pp 157–165