Reconfigurable Agile Manufacturing
Reconfigurable Agile Manufacturing (RAM) is a modern approach that enables manufacturers to quickly adapt their production systems to meet the ever-changing demands of a competitive, global marketplace. The concept emerged as a response to the limitations of traditional manufacturing, particularly in high-volume, low-variety environments. RAM emphasizes flexibility, allowing manufacturers to efficiently reconfigure their systems—such as rearranging equipment, reallocating labor, or retooling machinery—to produce customized products with minimal lead times and costs.
Key to achieving RAM is the integration of advanced technologies, including computer-aided design (CAD), computer-aided manufacturing (CAM), and enterprise resource planning (ERP) systems, which facilitate seamless information flow and process automation. This technological backbone supports rapid changes in production, enabling companies to manage workflows and materials effectively. Additionally, RAM incorporates strategies like delayed product differentiation, which helps in optimizing assembly processes by grouping similar tasks and postponing final product customization until necessary.
As manufacturers adopt RAM, they gain a competitive advantage by improving resource utilization, reducing inventory costs, and enhancing their ability to respond to market fluctuations. Overall, Reconfigurable Agile Manufacturing reflects a significant shift in how production systems can be designed to maximize efficiency and adaptability in an increasingly unpredictable economic landscape.
On this Page
- Overview
- Agile Manufacturing
- Applications
- Building a Reconfigurable Agile Manufacturing System
- ERP Software Integrates Data from the Enterprise
- Autodesk Products
- CIM Systems Integrate Manufacturing Technology
- Plugging the Enterprise into the Supply Chain
- Issues
- Developing Manufacturing Standards
- Standard for the Exchange of Product Model Data (STEP)
- Structuring the Product Development & Manufacturing Process
- Terms & Concepts
- Bibliography
- Suggested Reading
Subject Terms
Reconfigurable Agile Manufacturing
This article examines the forces of globalization and competition that are driving the need for manufacturing companies to be agile in order to stay competitive. The technological enablers of agility, which share a common reconfigurability, are explained including enterprise management systems, engineering systems, manufacturing systems, and manufacturing planning and control systems. The use of computer technology to schedule work in the manufacturing environment, to manage workflow, and to coordinate the movement of materials is also explained. The evolution of standards in data exchange for manufacturing is reviewed, along with the development of structured product design processes.
Keywords: Agile Manufacturing; Business-to-Business (B2B); Computer Aided Design (CAD); Computer Aided Engineering (CAE); Computer Numerical Control (CNC); Convertibility; Integrability; Modularity; Reconfigurable Manufacturing; Scalability; Supply Chain Systems
Overview
Not long ago, manufacturers had greater control over the supply chain because they controlled the pace at which products were manufactured and thus when they entered the supply chain. Globalization, competition, and technology have now converged to the point where manufacturers no longer set the pace and customers now rule the markets through their buying power and through purchasing from competing manufacturers or suppliers. Many manufacturers are now scrambling to meet customer demands for options, styles and features as well as quick fulfillment and fast delivery. Companies that have learned how to improve management of their production systems to meet demand, and changes in demand, have developed a competitive advantage and work hard to maintain that advantage (Uribe, Cochran, & Shunk, 2003).
As this evolution has taken place, the concepts of 'lean' and 'agile' have been applied in industry. Lean focuses on eliminating or reducing any activity or expenditure that does not add value to a company's operations (Pham & Thomas, 2005). Lean worked well enough in high volume, low variety and predictable environments (Harris, 2004). Agility was born out of necessity to deal with the issues of volatile markets and irregular demand patterns (Pham and Thomas, 2005). Manufacturing automation and computer aided design helped to drive the lean and agile movement by allowing reusability of designs and processes and to provide faster reconfiguration of manufacturing systems.
A reconfigurable manufacturing system (RMS) is designed for easy and fast changes in system configuration including rearrangement of equipment, reallocation of workers, or retooling of machines (Xiaobo, Wang & Luo, 2001). To maximize the competitive advantage of an RMS the manufacturing environment as a whole must be easily upgradeable and have the ability to assimilate new products and rapidly adjust system capacity as market demands change. The manufacturing environment should also have the ability to absorb new process technologies as well as new managerial practices (Singh, Khilwani & Tiwari, 2007).
Computer technology has enabled the agile movement by allowing reusability of designs and processes and to provide faster reconfiguration of manufacturing systems. Agility, and reconfigurable technology allows companies to produce customized products in a short time at low cost (Liao & Liao, 2008). The various computer technologies that improve efficiency and accuracy in manufacturing including CAE, CAD, CAM, CNC, ERP, and SCMS are becoming ubiquitous in manufacturing industries.
Agile Manufacturing
One of the major goals of agile manufacturing is to produce customized products in a short time at low cost (Liao & Liao, 2008). Agility in manufacturing helps to reduce material costs, maximize expenditures for human resources, minimize idle inventory, and improve facility or machine utilization (Anuziene & Bargelis, 2007). Flexibility is the key to productivity in reconfigurable agile manufacturing systems compared to previous designed manufacturing systems (Calvo, Domingo & Sebastiãn, 2008).
Agile manufacturing requires control of manufacturing systems as well as a design process that supports a modular manufacturing operation. Thus, to realize the benefits of an RMS and to achieve high levels of agility, consideration must be given to the design of products and components and how that design can best be manufactured in an agile environment (Kusiak & He, 1997).
Design for agility and agile manufacturing requires product grouping which allows for concurrent design and development of product families as well as faster and less expensive manufacturing and assembly systems and processes (McCurry & McIvor, 2002; Abdi & Labib, 2004). The level of agility achieved in a manufacturing environment can thus be improved by addressing the interrelationships between manufacturing components and the design of the items being manufactured (Yusuf & Adeleye, 2002; Jiang & Fung, 2003).
Another key factor in maximizing the success of agile reconfigurable manufacturing is the scheduling, or delaying of product differentiation in the machining and assembly process. With a delayed product differentiation strategy common and simple parts are created at the machining stage and put in queue for the assembly stage. This allows the assembly of different or customized products to be grouped and assembly postponed until the schedule requires or when a large enough number of customized products has accumulated so that reconfiguration is convenient or more cost effective (He & Babayan, 2002). Manufacturing scheduling helps to control costs and maintains profit margin which is absolutely necessary because, simply put, achieving agility without achieving profit is not a sustainable competitive strategy (Gunasekaran & Yusuf, 2002).
The basic axiom underlying the concept of agility is the ability to respond to change by implementing necessary reconfigurations of manufacturing systems and processes. Some changes can be anticipated such as the need to reconfigure for delayed assembly management. In other cases a company may plan or create change when installing new technologies. However, some changes such as disruptions in operations cannot be predicted because of supply problems or natural disasters. There are also circumstances that may not only be unpredictable but can also be unprecedented such as the rapidly widespread economic downturns or terrorist attacks that cause extensive physical, economic or social damages (Sharifi, Colquhoun, Barclay & Dann, 2001).
Applications
Building a Reconfigurable Agile Manufacturing System
Agility just does not happen by itself. An agile manufacturing firm needs information systems that inherently support agile business processes as well as agile manufacturing systems. (Weston, 1998; Ross, 2003). The use of computer numerical control (CNC) manufacturing equipment of all types eases reconfiguration of equipment and helps to minimize the cost of reconfiguration (Herrin, 1997; Lee, Harrison & West, 2005). In addition, the use of technologies that improve efficiency and accuracy can help reduce waste caused by defects in manufacturing, under-utilization of resources, or over production caused by poor planning (Shipulski, 2009).
Agile manufacturing companies rely heavily on automation, including:
- Enterprise information systems that are readily capable of supporting an agile manufacturing environment including sales, service, human resource management, logistics mostly commonly achieved through the use of enterprise resource planning (ERP) software suites.
- Computerization of the design and manufacturing process through computer aided design (CAD) and computer aided manufacturing (CAM), and computer aided engineering (CAE) software.
- Computer numerical control of individual pieces of equipment as well as groups of equipment through numerical control (CNC).
- Computer integrated manufacturing (CIM) systems connect and integrate the various machines and systems within the manufacturing process.
- Supply chain management systems that tie together all of the companies in a supply chain.
ERP Software Integrates Data from the Enterprise
ERP systems are integrated software suites that allow data to be used by various different modules within the system. ERP systems are constantly evolving and functionality has been expanded over the last twenty years. The ultimate goal of an ERP system is to provide cross-functional support to any department within an organization without that department needing to create new smaller systems to meet its information processing needs. The implementation of an ERP system often requires standardizing terminology across an organization so that enterprise-wide databases can be established and maintained (El Amrani, Rowe & Geffroy-Maronnat, 2006).
Over a period of several decades, Material Requirements Planning (MRP) systems for inventory control and later Manufacturing Resource Planning (MRP II) technology for shop-floor scheduling and coordination evolved and were integrated into large software suites that could help manage an entire enterprise. The newer ERP systems can help control and manage an entire manufacturing facility including production, purchasing, finance, human resources, engineering, and logistics (Kempfer, 1998).
Autodesk Products
The major technology driving changes in manufacturing processes during the last several decades has been computer-aided design, computer-aided manufacturing, and computer-aided engineering (Vasilash, 1998). These systems support the manufacturing process from the engineering phase through production. CAD/CAM workstations provide designers with the ability to use libraries of stored designs, information about parts, materials, tooling, and production. These systems help to achieve and maintain modularity, scalability, integrability, and convertibility which helps streamline design and manufacturing in an economically reusable manner, enabling manufacturers to be more agile (Singh, Khilwani & Tiwari, 2007).
CAE systems help engineers design a wide variety of products while CAD systems can help designers document and present their designs using three dimensional tools and parametric drawings. CAD systems provide specialized support for architects, civil engineers, controls designers, mechanical engineers, manufacturing environments, and fabrication shops. There are also systems that simulate and help to optimize part, mold, and tool designs before manufacturing begins, including designing factory layouts ("Autodesk Products," 2009).
CAM systems can translate the designs and specifications created with CAE and CAD systems into production process using computer numerical control (CNC) features and technologies which control individual as well as groups of machines that are required to produce an item. These systems can have a positive impact on manufacturing cost, quality, and delivery time. The deployment of equipment with an open architecture design eases system migration allowing new control features to be added as the equipment and the control technology evolves. CNC technology also provides greater accuracy and equipment can be operated at higher speeds (Herrin, 1997).
The computers that run the control software for manufacturing machines can also be networked, allowing manufacturing personnel to update systems software or change control programs over the network as opposed to one machine at a time. The CNC systems can also be set up to run self-diagnostics and provide error logs for problems that occur during operation.
CIM Systems Integrate Manufacturing Technology
CIM systems are combinations of hardware and software products that are used to integrate and control manufacturing activities. These systems help to bring together the abilities in CAD and CAM software, CNC machine tools, and material handling equipment ("CIM Support Software," 2009). As with CAD and CAM systems, a CIM system must provide flexibility and ease in reconfiguration in order to keep an enterprise agile (Farish, 2008; Jonsson & Sandgren, 2009).
In addition to controlling and scheduling configuration of manufacturing equipment, CIM systems can provide manufacturing support by electronically managing bill of materials, process flow, and bill of process for associated tools, consumables, and components. Materials flow can be managed for each job or product and with materials scheduled and routed to production stations and devices (Lin & Tsao, 2006).
Plugging the Enterprise into the Supply Chain
According to Kumar (2001), a supply chain is a "network of organizations with specialized activities that work together, usually in a sequential manner, to produce," distribute, sell, and service goods (p. 58). Supply chain systems support "networks of manufacturers and distributors, transportation and logistics firms, banks, insurance companies, brokers, warehouses and freight forwarders, all directly or indirectly attempting to make sure the right goods and services are available at the right price, where and when the customers want them" (Kumar, 2001, p. 58).
The chain does not end when the product is delivered. Kumar writes that through
In a supply chain environment the competitive success of a firm depends on how agile the whole chain is compared to those of competitors. To compete, all of the companies in a supply chain must be agile and deliver products that customers want at competitive price (Kumar, 2001).
Data business communication plays a key role in the modern supply chain system by supporting business-to-business (B2B) applications. Supply chain management systems (SCMS) are digitally enabled interfirm processes that integrate information flow, physical flow, and financial flow. Such systems require reliable networks capable of spanning the globe. Implementation of IT-based supply chain management systems has been shown to have a positive effect on procurement of materials for production as well as distribution, marketing, and sales after production (Richardson, 2006).
Issues
Developing Manufacturing Standards
Achieving agility in a manufacturing company requires both managers and production workers to understand the goal of agility and develop adaptable philosophies and attitudes towards business strategies as well as day-to-day operations. In addition, most aspects of a modern manufacturing environment are digital (Smith, 2007). Thus it is essential that both managers and production workers are trained in the use of appropriate technology that can reduce costs and improve quality, especially CAD/CAM/CAE/CNC systems.
The other necessary element is to understand and adhere to standards that can be used in information exchange, design, and manufacturing that can ease processes, reduce costs, and enable a company to neatly fit into the global manufacturing infrastructure. Managing and utilizing product information and knowledge in the production process enables companies to move faster and be more agile (Xie, Yang & Tu, 2008).
Standard for the Exchange of Product Model Data (STEP)
The Standard for the Exchange of Product Model Data (STEP) is an International Standards Organization (ISO) standard (ISO 10303) that specifies processes and structures to represent and exchange digital product information. STEP is structured in a way that all essential information about a product can be exchanged between users including CAD files and product data. The standard has a library of engineering definitions used for the product models in a wide range of industries. The common library covers geometry, topology, tolerances, relationships, attributes, assemblies, configuration and other characteristics. After STEP was developed the next phase of the standards development process included the addition of STEP NC, which enabled data from CAD systems to be used to input into CNC tools (Albert, 2000).
STEP replaced an older system, Initial Graphics Exchange Specification (IGES), a system that was used for over 30 years that primarily aided in exchanging data in graphics CAD files. However, early CAD systems used different operating systems and file structures and thus CAD files could not be used by companies that did not have the same type of equipment that the creator of the CAD work had used. Work began on STEP in 1980 and by 1984 organizations around the world began getting involved and ISO started a formal process to develop STEP (Albert, 2000).
There are several advantages in using STEP for exchanging and maintaining product data. The use of a standard format supports long-term archiving of technical data for products that have a long life including heavy equipment such as that used in construction or by the military. In addition, when everybody that works on or provides parts for the equipment receive the same technical data in a standard format, they know where to look for the specific type of information they need to fulfill their role in maintenance or repair (Moeller, 2000).
Structuring the Product Development & Manufacturing Process
Another aspect of manufacturing that contributes to agility is implementing a structured product development process. Several product development models have been used over the last seventy years. As STEP was implemented, product planning and modeling systems started to use it as a core set of product data to support design and manufacturing (Xie, Yang & Tu, 2008). The STEP Application Protocol 224 is a mechanical product definition for manufacturing process planning using machining features available in CNC systems. AP224 contains all the information needed to manufacture the required part, including the materials part geometry, dimensions and tolerances (Sharma & Gao, 2002).
Product development models are generally broken down into phases. These phases allow designers and producers to structure the development process and enable data management for all of the parts and steps in the manufacturing process. Phases generally include modularization, basic modeling objects, establishing relationship and attributes, identification and completion of constraints, and finally integrating all of the various modules that comprise a product (Gao, Aziz, Maropoulos & Cheung, 2003; Xie, Yang & Tu, 2008).
Workflow management in the manufacturing process is also essential for smooth operations as well as cost control (Rouibah, Rouibah, & Van Der Aalst, 2007). Agility in workflow management is achieved by using a dynamic scheduling process for determining when to reconfigure a system or when to use a specific machine on a job in order to meet deadlines and satisfy customer needs (Hwang & Choi, 2007). To improve workflow the manufacturing process must be planed including determination of sub-processes, machining stages, machine and cutting tool selection and the sequencing of machining operations (Nassehi, Liu & Newman, 2007).
Workflow planning and tool selection has become automated in many companies through the use of simulations and workflow management software (Kehris, 2009). Workflow analysis provides a map of individual tasks, that when combined result in a finished product and when executed in proper sequence result in efficiencies and cost savings (SanFilippo, 2007).
Material flows in a factory are also an important part of efficiency and cost control. One of the primary goals when designing material handling systems is that all work centers are provided with methods to move materials to and from the work center. Material handling systems can include ground conveyors, overhead conveyors, or automated monorails. Many of these systems are integrated into production scheduling systems or workflow management systems (Asef-vaziri & Ortiz, 2008).
The development of standards for product data and structured product development models have reduced cost and eased some of the inherent problems that manufacturers face in the design and production processes. These standards and models also enable companies to more readily fit into the global scheme of manufacturing and support their drive to be agile and more competitive.
The forces of globalization, competition, and technology have changed the way companies do business as producers and as consumers. As producers, companies tend to go through an evolutionary process in the philosophies and attitudes that management emphasizes and the lean and agile movements are two relatively recent examples of management perspectives.
Terms & Concepts
Business-to-Business (B2B) Applications: Applications software that supports interaction and transactions between business including supply chain systems, order enter and processing, and collaboration on design or fulfillment requirements.
Computer Numerical Control (CNC): A computer supported process of controlling manufacturing equipment with preprogrammed numerical sequences that dictate what a machine should do at every step in the manufacturing process.
Convertibility: The ability to transform the functionality of existing systems, machines, and controls to meet the requirements for manufacturing other products (Singh, Khilwani and Tiwari, 2007).
Integrability: The ability to rapidly and easily integrate existing systems of mechanical, informational, and control interfaces to control production systems (Singh, Khilwani and Tiwari, 2007).
Modularity: Provides the ability to utilize identical units to create product variants that can reduce the number of different parts required to manufacturer a product family (Singh, Khilwani and Tiwari, 2007).
Scalability: The ability to easily and quickly change production capacity by rearranging or reconfiguring existing machines or production systems (Singh, Khilwani and Tiwari, 2007).
Supply Chain Management Systems (SCMS): Applications software which is integrated into a communications network that enables organizations to communicate about and support their purchasing, sales, and shipping needs.
Bibliography
Abdi, M., & Labib, A. (2004). Grouping and selecting products: The design key of Reconfigurable Manufacturing Systems (RMSs). International Journal of Production Research, 42, 521-546. Retrieved August 4, 2009, from EBSCO online database, Business Source Premier. http://search.ebscohost.com/login.aspx?direct=true&db=buh&AN=11622815&site=ehost-live
Albert, M. (2000). STEP NC. Modern Machine Shop, 73, 70. Retrieved August 10, 2009, from EBSCO online database, Business Source Premier. http://search.ebscohost.com/login.aspx?direct=true&db=buh&AN=3324852&site=ehost-live
Anuziene, L., & Bargelis, A. (2007). Decision support system framework for agile manufacturing of mechanical products. Mechanika, 65, 51-56. Retrieved August 4, 2009, from EBSCO online database, Academic Search Complete. http://search.ebscohost.com/login.aspx?direct=true&db=a9h&AN=25690755&site=ehost-live
Aravind Raj, S.S., Sudheer, A.A., Vinodh, S.S., & Anand, G.G. (2013). A mathematical model to evaluate the role of agility enablers and criteria in a manufacturing environment. International Journal of Production Research, 51, 5971-5984. Retrieved November 15, 2013, from EBSCO Online Database Business Source Complete. http://search.ebscohost.com/login.aspx?direct=true&db=bth&AN=90503639&site=ehost-live
Asef-vaziri, A., & Ortiz, R. (2008). The value of the shortest loop covering all work centers in a manufacturing facility layout. International Journal of Production Research, 46, 703-722. Retrieved August 13, 2009 from EBSCO online database, Business Source Premier. http://search.ebscohost.com/login.aspx?direct=true&db=buh&AN=27541734&site=ehost-live
Autodesk Products. (2009). Retrieved August 4, 2009, from Autodesk Incorporated August 10, 2009. http://usa.autodesk.com/adsk/servlet/item?siteID=123112&id=8909451
Calvo, R., Domingo, R., & Sebastiãn, M. (2008). Systemic criterion of sustainability in agile manufacturing. International Journal of Production Research, 46, 3345-3358. Retrieved August 4, 2009 from EBSCO online database, Business Source Premier. http://search.ebscohost.com/login.aspx?direct=true&db=buh&AN=31643837&site=ehost-live
CIM Support Software. (2009). Internet Science and Technology Fair (ISTF). University of Central Florida's College of Engineering and Computer Science (UCF-CECS). Retrieved August 10, 2009 from Internet Science and Technology Fair (ISTF). http://istf.ucf.edu/Tools/NCTs/manufacturing/CIM%5fSupport%5fSoftware/
Doheny, M., Nagali, V., & Weig, F. (2012). Agile operations for volatile times. Mckinsey Quarterly, , 126-131. Retrieved November 15, 2013, from EBSCO Online Database Business Source Complete. http://search.ebscohost.com/login.aspx?direct=true&db=bth&AN=78031914&site=ehost-live
El Amrani, R., Rowe, F., & Geffroy-Maronnat, B. (2006). The effects of enterprise resource planning implementation strategy on cross-functionality. Information Systems Journal, 16, 79-104. Retrieved August 9, 2009 from EBSCO online database, Business Source Premier. http://search.ebscohost.com/login.aspx?direct=true&db=buh&AN=19215645&site=ehost-live
Farish, M. (2008). Our flexible friends [factory automation]. Engineering & Technology (17509637), 3, 62-67. Retrieved August 10, 2009 from EBSCO online database, Business Source Premier. http://search.ebscohost.com/login.aspx?direct=true&db=a9h&AN=34135793&site=ehost-live
Gao, J., Aziz, H., Maropoulos, P., & Cheung, W. (2003). Application of product data management technologies for enterprise integration. International Journal of Computer Integrated Manufacturing, 16(7/8), 491. Retrieved August 10, 2009, from EBSCO online database, Business Source Premier. http://search.ebscohost.com/login.aspx?direct=true&db=buh&AN=10665594&site=ehost-live
Gunasekaran, A., & Yusuf, Y. (2002). Agile manufacturing: A taxonomy of strategic and technological imperatives. International Journal of Production Research, 40, 1357-1385. Retrieved August 4, 2009, from EBSCO online database, Business Source Premier. http://search.ebscohost.com/login.aspx?direct=true&db=buh&AN=6510935&site=ehost-live
Harris, A. (2004). Reaping the rewards of agile thinking. Manufacturing Engineer, 83, 24-27. Retrieved August 4, 2009, from EBSCO online database, Academic Search Complete. http://search.ebscohost.com/login.aspx?direct=true&db=a9h&AN=15794151&site=ehost-live
He, D., & Babayan, A. (2002). Scheduling manufacturing systems for delayed product differentiation in agile manufacturing. International Journal of Production Research, 40, 2461-2481. Retrieved August 4, 2009, from EBSCO online database, Business Source Premier. http://search.ebscohost.com/login.aspx?direct=true&db=buh&AN=7008797&site=ehost-live
Herrin, G. (1997). Retrofitting and agile manufacturing. Modern Machine Shop, 70, 162. Retrieved August 8, 2009, from EBSCO online database, Business Source Premier. http://search.ebscohost.com/login.aspx?direct=true&db=buh&AN=9711110341&site=ehost-live
Hwang, H., & Choi, B. (2007). Workflow-based dynamic scheduling of job shop operations. International Journal of Computer Integrated Manufacturing, 20, 557-566. Retrieved August 13, 2009, from EBSCO online database, Business Source Premier. http://search.ebscohost.com/login.aspx?direct=true&db=buh&AN=25915387&site=ehost-live
Jiang, Z., & Fung, R. (2003). An adaptive agile manufacturing control infrastructure based on TOPNs-CS modelling. International Journal of Advanced Manufacturing Technology, 22(3/4), 191-215. Retrieved August 4, 2009, from EBSCO online database, Business Source Premier. http://search.ebscohost.com/login.aspx?direct=true&db=a9h&AN=16717943&site=ehost-live
Jonsson, M., & Sandgren, S. (2009). Creating the intelligent factory. SMT: Surface Mount Technology, 23, 18-28. Retrieved August 10, 2009, from EBSCO online database, Business Source Premier. http://search.ebscohost.com/login.aspx?direct=true&db=buh&AN=37197406&site=ehost-live
Kehris, E. (2009). Web-based simulation of manufacturing systems. International Journal of Simulation Modelling (IJSIMM), 8, 102-113. Retrieved August 13, 2009, from EBSCO online database, Academic Search Complete. http://search.ebscohost.com/login.aspx?direct=true&db=a9h&AN=41978021&site=ehost-live
Kempfer, L. (1998). Linking PDM to ERP. Computer-Aided Engineering, 17, 58. Retrieved August 8, 2009, from EBSCO online database, Academic Search Complete. http://search.ebscohost.com/login.aspx?direct=true&db=a9h&AN=1163573&site=ehost-live
Kumar, K. (2001). Technology for supporting supply chain management. Communications of the ACM, 44, 58-61. Retrieved August 13, 2009, from EBSCO online database, Academic Search Premier. http://search.ebscohost.com/login.aspx?direct=true&db=aph&AN=4771986&site=ehost-live
Kusiak, A., & He, D. (1997). Design for agile assembly: An operational perspective. International Journal of Production Research, 35, 157-178. Retrieved August 4, 2009, from EBSCO online database, Business Source Premier. http://search.ebscohost.com/login.aspx?direct=true&db=buh&AN=6484019&site=ehost-live
Lee, S., Harrison, R., & West, A. (2005). A component-based control system for agile manufacturing. Proceedings of the Institution of Mechanical Engineers — Part B — Engineering Manufacture, 219, 123-135. Retrieved August 4, 2009, from EBSCO online database, Academic Search Complete. http://search.ebscohost.com/login.aspx?direct=true&db=a9h&AN=15683658&site=ehost-live
Liao, C., & Liao, C. (2008). An ant colony optimisation algorithm for scheduling in agile manufacturing. International Journal of Production Research, 46, 1813-1824. Retrieved August 4, 2009, from EBSCO online database, Business Source Premier. http://search.ebscohost.com/login.aspx?direct=true&db=buh&AN=29956897&site=ehost-live
Lin, C., & Tsao, Y. (2006). Dynamic availability-oriented control of the automated storage/retrieval system. A computer integrated manufacturing perspective. International Journal of Advanced Manufacturing Technology, 29, 948-961. Retrieved August 10, 2009, from EBSCO online database, Academic Search Complete. http://search.ebscohost.com/login.aspx?direct=true&db=a9h&AN=21844971&site=ehost-live
McCurry, L., & McIvor, R. (2002). Agile manufacturing: 21 st century strategy for manufacturing on the periphery? Irish Journal of Management, 23, 75. Retrieved August 4, 2009, from EBSCO online database, Business Source Premier. http://search.ebscohost.com/login.aspx?direct=true&db=buh&AN=9641154&site=ehost-live
Moeller, G. (2000). Standard for the exchange of product model data (STEP). Program Manager, 29, 52. Retrieved August 10, 2009, from EBSCO online database, Business Source Premier. http://search.ebscohost.com/login.aspx?direct=true&db=buh&AN=3945212&site=ehost-live
Nassehi, A., Liu, R., & Newman, S. (2007). A new software platform to support feature-based process planning for interoperable STEP-NC manufacture. International Journal of Computer Integrated Manufacturing, 20, 669-683. Retrieved August 8, 2009, from EBSCO online database, Business Source Premier. http://search.ebscohost.com/login.aspx?direct=true&db=buh&AN=26641320&site=ehost-live
Pham, D., & Thomas, A. (2005). Fighting fit factories: Making industry lean, agile and sustainable. Manufacturing Engineer, 84, 24-29. Retrieved August 4, 2009, from EBSCO online database, Academic Search Complete. http://search.ebscohost.com/login.aspx?direct=true&db=a9h&AN=17127631&site=ehost-live
Richardson, V. (2006). Supply chain IT enables coordination. Industrial Engineer: IE, 38, 10. Retrieved August 13, 2009, from EBSCO online database, Academic Search Premier. http://search.ebscohost.com/login.aspx?direct=true&db=aph&AN=25170345&site=ehost-live
Ross, A. (2003). Creating agile supply chains. Manufacturing Engineer, 82, 18-21. Retrieved August 8, 2009, from EBSCO online database, Academic Search Complete. http://search.ebscohost.com/login.aspx?direct=true&db=a9h&AN=12261426&site=ehost-live
Rouibah, K., Rouibah, S., & Van Der Aalst, W. (2007). Combining workflow and PDM based on the workflow management coalition and STEP standards: the case of axalant. International Journal of Computer Integrated Manufacturing, 20, 811-827. Retrieved August 10, 2009, from EBSCO online database, Business Source Premier. http://search.ebscohost.com/login.aspx?direct=true&db=buh&AN=27217304&site=ehost-live
SanFilippo, E. (2007). Uses vary, benefits accrue, yet workflow remains something of a mystery. Manufacturing Business Technology, 25, 34-36. Retrieved August 13, 2009, from EBSCO online database, Business Source Premier. http://search.ebscohost.com/login.aspx?direct=true&db=buh&AN=24502002&site=ehost-live
Sharifi, H., Colquhoun, G., Barclay, I., & Dann, Z. (2001). Agile manufacturing: A management and operational framework. Proceedings of the Institution of Mechanical Engineers — Part B — Engineering Manufacture, 215, 857-869. Retrieved August 4, 2009, from EBSCO online database, Academic Search Complete. http://search.ebscohost.com/login.aspx?direct=true&db=a9h&AN=6705727&site=ehost-live
Sharma, R., & Gao, J. (2002). Implementation of STEP application protocol 224 in an automated manufacturing planning system. Proceedings of the Institution of Mechanical Engineers — Part B — Engineering Manufacture, 216, 1277-1289. Retrieved August 10, 2009, from EBSCO online database, Business Source Premier. http://search.ebscohost.com/login.aspx?direct=true&db=a9h&AN=7344146&site=ehost-live
Shipulski, M. (2009). Resurrecting manufacturing. Industrial Engineer: IE, 41, 24-28. Retrieved August 10, 2009, from EBSCO online database, Academic Search Complete. http://search.ebscohost.com/login.aspx?direct=true&db=a9h&AN=42832321&site=ehost-live
Singh, R., Khilwani, N., & Tiwari, M. (2007). Justification for the selection of a reconfigurable manufacturing system: a fuzzy analytical hierarchy based approach. International Journal of Production Research, 45, 3165-3190. Retrieved August 4, 2009, from EBSCO online database, Business Source Premier. http://search.ebscohost.com/login.aspx?direct=true&db=buh&AN=25192109&site=ehost-live
Smith, F. (2007). Digital manufacturing takes off. (Cover story). Control Engineering, 54, 38-44. Retrieved August 13, 2009, from EBSCO online database, Academic Search Complete. http://search.ebscohost.com/login.aspx?direct=true&db=a9h&AN=26317281&site=ehost-live
Taylor, A., Taylor, M., & McSweeney, A. (2013). Towards greater understanding of success and survival of lean systems. International Journal of Production Research, 51, 6607-6630Retrieved November 15, 2013, from EBSCO Online Database Business Source Complete. http://search.ebscohost.com/login.aspx?direct=true&db=bth&AN=91967889&site=ehost-live
Uribe, A., Cochran, J., & Shunk, D. (2003). Two-stage simulation optimization for agile manufacturing capacity planning. International Journal of Production Research, 41, 1181-1197. Retrieved August 4, 2009, from EBSCO online database, Business Source Premier. http://search.ebscohost.com/login.aspx?direct=true&db=buh&AN=9687813&site=ehost-live
Vasilash, G. (1998). Networking the organization: Ford's CAD/CAM/CAE/PIM strategy. Automotive Manufacturing & Production, 110, 52. Retrieved August 9, 2009, from EBSCO online database, Business Source Premier. http://search.ebscohost.com/login.aspx?direct=true&db=buh&AN=988494&site=ehost-live
Weston, R. (1998). Integration infrastructure requirements for agile manufacturing systems. Proceedings of the Institution of Mechanical Engineers — Part B — Engineering Manufacture, 212, 423-437. Retrieved August 8, 2009, from EBSCO online database,Academic Search Complete. http://search.ebscohost.com/login.aspx?direct=true&db=a9h&AN=6699304&site=ehost-live
Xiaobo, Z., Wang, J., & Luo, Z. (2001). A stochastic model of a reconfigurable manufacturing system. International Journal of Production Research, 39, 1113-1126. Retrieved August 4, 2009, from EBSCO online database, Business Source Premier. http://search.ebscohost.com/login.aspx?direct=true&db=buh&AN=4319012&site=ehost-live
Xie, S., Yang, W., & Tu, Y. (2008). Towards a generic product modelling framework. International Journal of Production Research, 46, 2229-2254. Retrieved August 10, 2009, from EBSCO online database, Business Source Premier. http://search.ebscohost.com/login.aspx?direct=true&db=buh&AN=29991929&site=ehost-live
Yusuf, Y., & Adeleye, E. (2002). A comparative study of lean and agile manufacturing with a related survey of current practices in the UK. International Journal of Production Research, 40, 4545-4562. Retrieved August 4, 2009, from EBSCO online database, Business Source Premier. http://search.ebscohost.com/login.aspx?direct=true&db=buh&AN=8952735&site=ehost-live