Benefits Of Smart Manufacturing

Published Date: 02 Nov 2017

Introduction :

The key indicators of any industry are Quality, Delivery & Cost. No matter how naïve it may sound , industrial world is and will be trying to achieve the best of these qualities to sustain , grow & surpass competition.

Other deliverables like cutomer support, responsiveness, innovativeness etc are just mere images of the above mentioned indicators. Competion is ineviatable in any field of indutry, It is a neverending race to be ahead of your competition in all aspects . This attitude defines the very essence of business world. One of such fields is manufacturing sector, the oldest and most complicated fields which has always been the very core of the world economy. My report will specifically emphasizes on industrial production which concentrates on converting raw material into finished goods at a large scale. With these points in mind we can recon now that the line between software and hardware is very thin . Both are inevitable parts of each other in the modern manufacturing setup. The world was on the threshold of a new era of innovation and change with the rise of the Internet and the next big leap will be integrating the oldest sector of industry with the most advanced technology of intetnet communication.

http://www.automationworld.com/sites/default/files/styles/lightbox/public/GE.IndustrialInternetRevolution.jpgCourtesy GE.com

It is achieved by integrating global industrial systems with the power of advanced computing, analytics, low-cost sensing and new levels of connectivity permitted by the Internet. These innovations promise greater speed , productivity , flexibility and efficiency to industries.

Summary :

The current economic crisis was a awakening for the manufacturing industry where the market demanded for efficient and flexible processes. This in particular required manufacturing systems and adminstrative processes yo be meshed with each other by means of IT systems to optimize capacity utilization of machines and lines along with the ability to respond rapidly to unexpected stoppages, quality problems, raw material shortages , inventory buidup etc and to minimize the effects of these on business. Internet paves a new path for achieving this faster and effectively.

This can be achieved by combining the following three elements

INTELLIGENT MACHINES: Connecting array of machines, facilities, and networks with advanced sensors, controls and software applications.

ADVANCED ANALYTICS: Harnessing the power of physics-based analytics, predictive algorithms, automation and deep domain expertise in material science, electrical engineering and other key disciplines required to understand how machines and larger systems operate.

PEOPLE AT WORK: Connecting people, whether they be at work in factory or on the move, at any time to support more intelligent design, operations, maintenance as well as higher quality service and safety.

http://www.ge.com/sites/all/themes/ge_2012/assets/img/chapters/building_industrial_internet/industrial_internet_wide.gifCourtesy GE.com

This metamorphasis helps in obtaining valuable real-time data instanly online via internet. This data can be analyzed by advanced online anaytics to assist in decision making process. Swift data gathering and immediate decisions makes a manufacturing setup more flexible, productive and efficient in rapidly changing scenarios. Building smart manufacturing systems starts with embedding sensors and other advanced instrumentation in an array of machines from the simple to the highly complex. This allows the collection and analysis of an enormous amount of data, which can be used to improve machine performance,predict breakdowns , tools & fixture life study etc and inevitably the efficiency of the systems and networks that link them. Even the data itself can become smart, instantly knowing which users it needs to reach.

Nowadays, the capacity of reconfiguration has become a major issue for improving the functioning of industrial processes. Indeed, today the main objective is to adapt quickly in order to start a new production or to react in a failure occurrence . Intelligent manufacturing systems has both flexibility and reconfigurability, in fact this concept brings more thana few ideas of software intelligence meanings, which con-templates characteristics such as autonomy, decentralization, fexibility, reliability, effciency, learning, and self regeneration.

Methodology:

The industrial machinery and production lines nowadays are equipped with high –tech communication, networking devices, robotics and interfaces which can perform assigned tasks and in the meantime provide real-time data. But the data generated is so huge, hard to interpret & takes time to reach the right administrative departments for decision making process.

http://files.gereports.com/wp-content/uploads/2012/11/industrial-internet-data-loop.jpgCourtesy GE.com

The methodology of achieving this is illustrated in the above cycle of processes.

Step 1: Integrate all the verticals in a factory because interfaces are the building blocks of smart manufacturing systems. The level of industrial automation with decentralized functions is a favouring factor for implementing smart manufacturing. The production process & administrative information systems such as Enterprise resource planning(ERP), manufacturing execution sstems (MES) and automation systems have to be linked efficiently in a modern factory . Standardisation is the driving factor in forming the foundation for this integration.

Courtesy Intel.com

Step 2: Integration of individual cells or lines. In order to achieve more productive integration of information and materials streams requires continuous "machine to machine" communication systems in addition to optimising business and IT process. The prerequisite for this is a poweful IT system with local control software and a wealth of communication options.

Step 3: Install data security systems. Data security will be an important aspect in this system as senstive and confidential data will be transferred and analyzed over internet. Both production cells and industrial IT systems must be sufficient firewalled and necessary measures have to be taken to fend off threats.

Step 4: System integration using system neutrals or bidirectional translators to exchange data between machines and setups.

Step 5: Gathering real-time data continuosly into a server or cloud and installing complex algorithms to analyze these data into a sensible formats and distribute the same to relavent departments .

Every machine/device with instrumentation & networing will produce large quantities of data that can be transferred via the Industrial Internet network to remote machines and users. An important part of the implementation of the smart manufacturing is to determine which data should remain on devices and which data is transferred to remote locations for analysis and storage.

Determining the degree of local data residency is one of the keys to ensuring the security of the smart manufacturing. Other data streams will be transferred remotely so that they can be visualized, analyzed, augmented and acted upon, as appropriate, by people at work or on the move. Over time, these data flows provide a history of operations and performance that enables operators to better understand the condition of the critical components of the plant. Operators can understand how many hours a particular component has been operating and under what conditions. Analytic tools can then compare this information to the operating histories of similar components in other plants to provide reliable estimates of the likelihood and timing of component failure. In this manner, operating data and predictive analytics can be combined to avoid unplanned outages and minimize maintenance costs. All of these benefits come from machine instrumentation using existing information technologies and doing so in ways that enable people to do their jobs more effectively. This is what makes the widespread deployment of intelligent devices so potentially powerful.

In an era when it is increasingly challenging to squeeze more productivity from high-performance machines, the broad deployment of intelligent devices holds the potential to unlock additional performance and operational efficiencies.

Benefits of Smart Manufacturing:

The potential benefits of smart manufacturing systems are vast. . As an increasing number of machines and devices join the this initiative, the synergistic effects of widespread machine instrumentation can be realized across fleets and networks.

Network Optimization:

The operation of interconnected machines within a system can be coordinated to achieve operational efficiencies at the network level. Smart systems are also well suited for route optimization within transportation networks. Interconnected vehicles will know their own location and destination, but also can be alerted to the location and destination of other vehicles in the system—allowing optimization of routing to find the most efficient system-level solution.

Maintenance Optimization:

Optimized & low-cost machine maintenance across production lines can also be facilitated by smart systems. An comprehensive view across machines, components and individual parts provides a overview on the status of these devices and enables the optimal number of parts to be delivered at the right time to the correct location. This minimizes parts inventory requirements and maintenance costs, and provides higher levels of machine reliability. Smart system maintenance optimization can be combined with network learning and predictive analytics to allow engineers to implement preventive maintenance programs that have the potential to lift machine reliability rates to unprecedented levels. Establishing broad system-wide intelligence can also assist in more rapidly and efficiently restoring systems recovery after major shocks.

Learning:

Network learning effects are another benefit of machine interconnection with a system. The operational experiences of each machine can be combined into a single information system that accelerates learning across the machine portfolio in a way that is not possible with a single machine. Building out intelligent systems harnesses the benefits of widely deploying intelligent devices. Once an increasing number of machines are connected within a system, the result is a continuously expanding, self-learning system that grows smarter over time.Each machine can be aggregated into a single information system that accelerates learning across the machine portfolio.

Intelligent Decisioning :

Intelligent Decisioning occurs when enough information has been gathered from intelligent devices and systems to facilitate data-driven learning, which in turn enables a subset of machine and network-level operational functions to be transferred from operators to secure digital systems. Consider fully instrumented networks of facilities across wide geographic locations. Operators need to quickly make thousands of decisions to maintain optimal system performance.. The burden of complexity is transferred to the digital system. These capabilities will facilitate the ability of people and organizations to do their jobs more effectively.

Big data Analytics:

As the intelligent pieces are brought together, the smart manufacuring brings the power of "big data" together with machine-based analytics. Traditional statistical approaches use historical data gathering techniques where often there is more separation between the data, the analysis, and decision making. As system monitoring has advanced and the cost of information technology has fallen, the ability to work with real-time data has been expanding. Greater capability to manage and analyze high frequency real-time data brings a new level of insight on system operations. Machine-based analytics offer yet another dimension to the analytic process. Using a combination of physics- based methodologies, deep sector-specific domain expertise, increased automation of information flows, and predictive techniques, advanced analytics can be joined with the existing suite of "big data" tools.

Disadvantages or Threats :

As a new concept smart manufacturing is prone to threats internally and externally. For the implementation of smart manufacturing we need a systematic approach of change management, training and level of awareness in the production lines. The biggest disadvantage if this is adapting to this system can be time consuming and costly affair which need continuous effort and commitment from the management and workforce.

Conclusion:

Smart manufacturing is thought to be the next revolution in the modern manufacturing . It needs development of many softwares, networking and communication devices, regulations, standards and level of understanding to realize in reality . It’s a brave step which major corporations such as GE and Intel have taken up in this year and as a technology enhusiast I would definetly be a part and contribute for this revolution. Smart manufacturing is a big leap which requires billions of dollars of research & development investments which inturn adds to the economy of a country by supporting industrial growth.