Showing posts with label Equipment. Show all posts
Showing posts with label Equipment. Show all posts

Thursday, June 16, 2011

Leading Global Supplier To Original Equipment Manufacturers Selects Kofax For Its Invoice Processing Solution

IRVINE, CALIF.--(BUSINESS WIRE)--

Kofax plc (LSE: KFX), the leading provider of document driven business process automation solutions, today announced it will provide an invoice processing solution to a leading global supplier to original equipment manufacturers and their aftermarkets. The value of the contract to Kofax exceeds $500,000.

The customer, which provides products and services to manufacturers in the automotive, commercial vehicle, marine and other industries, will implement Kofax Capture, Kofax Transformation Modules and Kofax Front Office Server to capture, validate and extract information from over 900,000 invoices it receives annually. By enabling the company's front office employees to automatically scan invoices, the Kofax solution will help the company reduce costs and accelerate its invoice approval and payment processes while maintaining optimal relationships with its myriad of suppliers.

"Manufacturers receiving invoices from numerous vendors benefit from a unified capture solution that reduces the costs and errors associated with manual invoice processing," said Alan Kerr, Executive Vice President of Field Operations at Kofax. "Capturing invoices in a consistent manner as they are received allows our customers to immediately initiate their back office accounts payable processes, leading to improved efficiency and significant cost savings."

Kofax Capture provides industry leading scan-to-archive capabilities by scanning documents and forms to create digital images, extracting index data for retrieval purposes and delivering the images and associated data to a variety of repositories and applications. This can significantly reduce retrieval costs while improving better regulatory and compliance efforts. Kofax Capture is flexible and scalable, enabling customers to define where and how images are captured and indexed, whether in a home office, remote branch or back office data center.

Kofax Transformation Modules (KTM) adds document and form classification, page separation, challenging data extraction and validation capabilities to Kofax Capture to drive robust scan-to-process applications. By automating what were previously labor intensive, error prone and time consuming tasks, Kofax Transformation Modules can significantly reduce labor costs, improve information quality and accelerate business processes.

Kofax Front Office Server extends existing Kofax Capture business processes to customer facing employees seeking to initiate transactions, workflows and capture processes at the earliest point of contact to leverage existing resources in remote or branch offices. This office automation solution reduces process latency and eliminates the time and cost of shipping documents to centralized processing centers.

About Kofax

Kofax plc (LSE: KFX) is the leading provider of document driven business process automation solutions. For more than 20 years, Kofax has provided award winning solutions that streamline the flow of information throughout an organization by managing the capture, transformation and exchange of business critical information arising in paper, fax and electronic formats in a more accurate, timely and cost effective manner. These solutions provide a rapid return on investment to thousands of customers in financial services, government, business process outsourcing, healthcare, supply chain and other markets. Kofax delivers these solutions through its own sales and service organizations, and a global network of more than 700 authorized partners in more than 60 countries throughout the Americas, EMEA and Asia Pacific. For more information, visit www.kofax.com.

"Kofax" is a registered trademark in the US, the EU and other regions. All other trademarks and registered trademarks are the property of their respective owners.


Copyright Business Wire 2011

Saturday, November 13, 2010

Context and Learning to Programming of Intelligent Equipment

Context and Learning based Approach to Programming of Intelligent Equipment pdf cover page
.. of Automation of Production in Machine Building, … and Computational Intelligence in development of programming languages for industrial applications such as industrial robots … Context and Learning based Approach to Programming of Intelligent Equipment Andrey V. Gavrilov Department of Automation of Production in Machine Building, Novosibirsk State Technical University Karl Marx Av., 20, Novosibirsk 92, 630092 Russia Andr_gavrilov@yahoo.com Abstract In this paper novel approach for programming of intelligent equipment …

One of most actual problems in development of intelligent systems for manufacturing is human- machine interface. Two kinds of such interfaces are known, oriented on programming and learning respectively. Programming is used usually for industrial robots and other technological equipment. Learning is more oriented for service and toy robotics. There are many different programming languages for different kinds of intelligent equipment, for industrial robots-manipulators, mobile robots, technological equipment [1, 2]. The re-programming of industrial robotic systems is still a difficult, costly, and time consuming operation. In order to increase flexibility, a common approach is to consider the work- cell programming at a high level of abstraction, which enables a description of the sequence of actions at a task-level. A task-level programming environment provides mechanisms to automatically convert high- level task specification into low level code. Task-level programming languages may be procedure oriented [3] and declarative oriented [4, 5, 6, 7] and now we have a tendency to focus on second kind of languages. But in current time practically all programming languages for manufacturing are deterministic and not oriented on usage of learning and fuzzy concepts like in service or military robotics. But it is possible to expect in recent future reduce of difference between industrial and service applications. For example, known plans of Toyota Inc. to employ humanoid robots in automobile manufacturing. So it seems interesting and perspective to apply achievements of AI and Computational Intelligence in development of programming languages for industrial applications such as industrial robots or technological equipment. In this paper we suggest novel approach to programming of robots and technological equipment based on usage of context and learning and so oriented on usage of natural language for learning. In this approach we do not distinguish learning and programming combining in one system declarative (description of context) and procedural knowledge (routines for processing of context). Also here new Context Based Language for Robot (CBLR) is proposed and elements of one are described. This suggested approach is based on research of author during development of system software for transportation industrial robots based on learning [8, 9] and development of software for searching of documents by natural language query [10]. 2. Previous example of usage of similar approach for programming of transportation industrial robots… The language BLRP consisted of following groups of commands: 1) For assignment of context, 2) For control of moving, 3) For control of execution of routines, 4) For definition of conditions, 5) For determination of points in environment (service area) of robot, 6) For description of state of robot and technological equipment, 7) Serving commands. Architecture of software developed for robot consists of subsystems for programming, checking and execution of routines (figure 1). Context included main following parameters: 1) X, Y, Z - coordinates of point, 2) Description of condition operator, 3) State of equipment, 4) State of robot, 5) Number of link of robot, 6) Number of cell of equipment, 7) Number of object. Number in these parameters means identifier. Fig. 1. Architecture of software for transport robot. Programming in this system was replaced by learning. Result of one was knowledge base with associations between words of natural language and sequences of commands for description of context and….