Manufacturing Operations Management Talk

Manufacturing’s Evolution to the Digital Business World is Well on Its Way

-  What I learned at the 2015 Gartner Supply Chain Conference

There is no denial that the manufacturing industry is in a period of evolution to support a new digital business world. New companies are popping up with new business models, some companies will slowly be left behind, and a few companies will figure out how to transform and adapt to take advantage of the new markets and business opportunities. Companies that do not evolve will not be able to compete against new business models like mass customization and product-as-a-service. Examples of companies on this evolutionary path were presented at this year’s Gartner Supply Chain Conference in Phoenix, Arizona.

In this new digital manufacturing world, a Manufacturing Execution System (MES) is a requirement, not an option. An integrated MES system is needed for a digital thread into the plant floor and the supply chain in order to streamline and automate procedures to support use cases like single unit work orders where each order in the sequence builds a different custom product configuration. MES users are reporting more than cost and quality improvements. They are experiencing improvement in employee engagement and flexibility.

 The Industrial Internet of Things (IIoT) is real, not only within plants but also into the supply chain. Gartner is predicting 30% more connected devices every year with more open standards. Current IIoT examples are merely providing a glimpse into the future potential of the Smart Factory. The roadmap for the Internet of Everything (IoE) in the connected supply chain includes increased visibility, proactive issue resolution, enhanced customer experience, data anytime and anywhere, and multi-tier value chain collaboration. 

 

The complexity of mass customization requires tighter integration of Product Lifecycle Management (PLM), MES and Supply Chain Management (SCM) systems. Starting with product design and manufacturing simulations, taking advantage of 3D printing and robotics and smart manufacturing machines and processes that can setup themselves to each product’s custom configuration. The factory of the future will be focused on capability rather than capacity. The next level of integration in the digital thread will require more CAD vendor openness and support for standards like ISO10303.

Many examples were given showing great strides in the connected supply chain for some industries for demand sensing and inventory visibility, but Quality is currently a missing link in supply chain management. There is a great opportunity to improve the digital thread for managing quality, not just for transmitting requirements and data collection but also for handling issues and corrective actions more efficiently in a multi-tier supply chain network.

Companies that want to transform will need more “Mode 2” versus “Mode 1” type of business investments.

* Mode 1: Reduce cost, increase capacity and utilization, plan driven, setup for batch production, proprietary integrations
* Mode 2: Focused on agility, capability, demand driven, order qty 1, integration of IT and OT  

 

 

 

 Organizations must appoint change champions and start working on the following types of initiatives:

• Transforming the workforce to embrace learning new skills, flexible work skills and performance transparency across departments and divisions of the organization and partner network
• Moving from custom and proprietary integration to open standards to support the Industrial Internet of Things and Smart Machines
• Convergence of IT and OT (Operations Technology) integrating plant floor, enterprise systems, mobile, cloud and social technologies
• Smart products that can store and exchange information with smart machines and smart manufacturing processes about their configuration and state
• Taking business and manufacturing intelligence to the next level developing predictive and prescriptive analytic capabilities

If you have access to the Gartner presentations, the following is a list of my favorite presentations from the conference:

• “Operational Strategies for a Digital Business World,” Dwight Klappich, William McNeil “Product Innovation Platforms: Managing Complex Product Life Cycles,” Marc Halpern
• “The Emperor’s New Clothes and the Factory of the Future,” Simon Jacobson
• “How to Avoid the Pitfalls of MES Implementations,” Rick Franzosa
• “Quality: The Missing Link in Your Supply Chain Strategy”, Simon Jacobson, Gartner SCC 2015 Conference Presentation
• “Supplier Quality 2017: The Multitier Quality Frontier,” Ray Barger
• “Leading Supply Chain in a Digital Business,” Mike Burkett
• “Internet of Things in Supply Chain: What’s Real Now?” Mike Burkett

 

Do We Have Manufacturing Problems Looking for Smart Solutions?

If you are responsible for manufacturing operations improvements, you can probably dream of a few solutions that would make some hard production problems go away or take your operations to a new level of efficiency. When you hear titles like “Smart Manufacturing”, it is easy to hope that these initiatives will yield some of those dream solutions.

I was in brainstorming workshops a few weeks ago discussing the next generation of platforms and integrated systems for Smart Manufacturing. The discussions around potential new enhanced processes were very fructiferous, so I am sharing a few ideas I personally found very interesting.

• Manufacturing machines could set up themselves and select the right configuration files based on auto identifying the product’s configuration from an RFID tag. 
• More defects could be detected in-process through robotic CMM that read the product configuration RFID, read the latest product definition directly out of CAD files, and automatically measure critical dimensions as the material is cut or product is assembled. 
• Processes that depend on final product testing to ensure product quality can cause a lot of scrap waste when the final product does not meet specifications. It would be more efficient to have improved sensors that would monitor the product recipe as ingredients are added and transformed with feedback processes that would adjust the process automatically to account for material, process or environment variables. 
• Variation within control specs/limits of raw material properties causes shifts in final product quality. We want to auto adjust our process or recipe to accommodate variations in materials instead of having to demand costly higher accuracy in material specifications. Material would come with actual measured properties instead of us assuming that they meet a specification. 
• Employee safety could be improved by using sensors and automating test procedures involving hazardous materials or processes.

It is easy to see that these types of processes would yield many benefits including:

• Quality consistency of realized products with less waste/scrap and rework
• Less labor of non-value added tasks like setup, testing, and fixing 
• Lower cost for manufacturing one custom configured piece at a time
• Improved personnel safety

But is it possible to reduce the cost of achieving these levels of automation? Will “Smart Manufacturing” ideas and new technologies get us there? Or will it always be easier to design human sensing and decision making into these processes? Some of the challenges
to achieving these levels of automation include:

• High cost of sensor and analysis technology 
• Lack of integration standards between hardware, network and software tiers 
• Lack of models that link available measurements/inputs to desired output properties
• Lack of trained resources in the factory to implement new technology

Can we can make these technologies more affordable and easier to implement. If we can, what problems would you want to address in your factory with the new generation of Smart Manufacturing technologies and integration standards?

 

Where Do Manufacturing Strategists get their Information?

 A German survey showed that strategists working on Industrie 4 and related initiatives like IIoT and Smart Manufacturing are getting their information this way: 

 

These numbers probably also apply to Manufacturing IT professionals working on manufacturing operations management systems. Where do you get your information? 

Reference: 

"How far are we? Industry 4.0", hannovermess.de whitepaper, 2015

 

 

Future Smart Manufacturing and IIoT Systems will Leverage Cloud Services

A little background on cloud services

Before diving into the manufacturing system specific topic, it is necessary to clarify the term “cloud
services”. There are multiple cloud platform models in use today but this article will focus on the
opportunities provided by leveraging new commercial cloud component services in a mix with on-premise software versus looking at moving the entire information system to the “cloud”.

Types of cloud services:
• Infrastructure-as-a-Service (IaaS) – Virtual machine services accessed over the network providing
computational and storage capabilities
• Software-as-a-Service (SaaS) – Software applications (such as PLM, ERP, Inventory Control, or CRM)
provided as a service from the cloud
• Platform-as-a-Service (PaaS) - Platform software services (including application server, database
server, web user interface framework, workflow orchestration services, and enterprise service bus
middleware) on which to build custom web service-based applications for the enterprise
• Component-as-a-Service (CaaS) - Commercial cloud delivered technology, data and connectivity services (such as identity verification, app marketplace, supply chain data exchanges, analytical engines and document storage) that can be incorporated into on-premise or cloud-based custom enterprise applications. In contrast to regular web sites focused on interacting with human users, these cloud component services provide APIs to exchange data directly with applications.

From a financial point of view these cloud services can be very exciting because they are provided
under term and usage pricing models. But in addition to the new pricing models that are making new technology adoption more affordable, we should also get excited about the new functionality and integration options enabled.

The benefits of using SaaS and IaaS have been covered in many general information technology articles, but I haven’t seen much discussion on the potential for PaaS and CaaS for manufacturing systems. I also want to propose that a mixed model leveraging a combination of distributed on-premise applications and cloud component services should provide the best framework for future manufacturing systems.

Cloud services and new standards evolving around the Industrial Internet of Things (IIoT) are rendering the old division between automation, IT and business obsolete. The availability of quality cloud component services that are easy to assemble into a custom application will change the future of the Information Technology (IT) department. Other enterprise departments will be able to assemble applications they need themselves on a UI, workflow and integration framework. The IT department will change from focus on developing, installing and supporting software applications, to focus on providing guidelines and a framework for assembling integrated enterprise applications. The framework provided by the IT department will include security schemes, brokering of the mix of commercial IaaS, SaaS, PaaS and CaaS, and integration standards that the enterprise will use.

The question should not be whether or not our manufacturing system will be on the cloud, but instead figuring out how much of our manufacturing system will be on the cloud to maximize the benefits to our organizations and customers. Cloud computing is here to stay providing new software delivery models and information technology options. A mix of on-premise plus on-cloud solutions will most likely provide the best landscape for future manufacturing systems, and in fact some software vendors are already moving in that direction. Business critical data, and speed/availability sensitive applications can be maintained on-premise. Integrated enterprise systems can leverage a layered and distributed landscape of on-premise applications and on-cloud components integrated via SOA (service-oriented architecture) interfaces. The new IT options enabled by cloud services will become more affordable and easier to maintain which will be of great interest to smaller organizations with a smaller IT staff.

A hybrid on-premise and on-cloud model for manufacturing systems

What would this mixed on-premise and on-cloud model look like? I could see it having: (a) an enterprise level business process management (BPM) and workflow orchestration engine, (b) integration mechanisms to enable receiving and sending information between the BPM layer and other layers from machine to plant to supply chain, (c) several persistent layers of data with different precision and time horizons for data needed at the controller level versus business level, and (d) a combination of role specific and enterprise system applications designed to optimize the job of each user role and function in the overall integrated enterprise system.

 

Manufacturing systems orchestrate interdepartmental processes

The Manufacturing Operations department cannot effectively be managed as an island isolated from other enterprise departments including Engineering, Supplier Management, Quality Management, Human Resources, Facilities Management and Financial Management. We need effective ways to create information threads for complete business processes across departments that do not depend on manual translation of information. We currently run many interdepartmental business process via paper, email, and with many manual interpretations and translations of data inputs to outputs along the way. These manual interdepartmental business processes are error prone and cannot scale to handle higher volume of transactions.

Business Process Management (BPM) and Workflow tools can be used to string together business processes that span across enterprise departments. For example, managing the release of a revision to a product design from engineering to supply chain to revise component parts, to quality to revise inspection requirements, to fabrication to revise NC programs, and to production to revise assembly procedures. All these processes need to be orchestrated so that they cut in at the right time so the right version of the components are available for production with the right machine and inspection instructions.

An ideal manufacturing system platform would facilitate (a) integration throughout different functional layers including automation control, operations management, equipment maintenance, supply logistics, and business management layers, and (b) integration throughout parallel management systems including physical, human, information, sustainability, economic, social, and regulatory systems.

Cloud component services for manufacturing systems

Types of cloud component services that could be leveraged in a manufacturing system include:
• Data Services including Data Storage, Data Format Translation, Document Repository
• Analysis Services including statistical correlation or predictive analysis that does not have to run
real-time along with the run of a machine process
• Specialized Apps including Document Authoring and File Viewers for specific CAD formats
• Industry Market Places to acquire parts and materials more effectively
• Supply Chain Data Exchanges for controlled communications tied to contracts between multiple tiers of suppliers in the product value chain
• Weather Services to optimize energy utilization settings at the factory
• Product Transportation and Distribution Hubs to get the product to the distribution channel and
customer in the most efficient manner
• Identity Verification Services to make sure the person or machine trying to exchange information is authorized to access the information requested.
• Printing Services in case you must still print something at the corner printing store : )

Distributed layered manufacturing system between business and machines

Could we just move the whole manufacturing system to the cloud? Perhaps for some cases, however at some plants more intimate controller-machine interactions should probably remain on-premise near the machine. For a more distributed and layered system, the general MOM (Manufacturing Operations Management) functions of Work Order Management, WIP Management, Quality, Maintenance, etc. could be provided by applications hosted in a cloud service that would interface to multiple lower level “Smart Machine Controller Appliances” at the shop floor.

The Internet of Things (IoT) interconnects “smart” devices via standard Internet Protocol Suite
(TCP/IP). The Industrial Internet of Things (IIoT) has to strive for the same goal for a new generation of “smart” machines. New IIoT standards should not maintain the old networking standards (Profibus, Fieldbus, etc) used for older machine automation controls. To achieve this goal we might need an intermediary application layer that will translate “smart” communications to older “not as smart” controllers, machines and sensors that do not speak the new integration language standards directly.

In the IIoT, the proliferation of connected smart machines, devices, and sensors can result in an
explosion of data. A distributed layered system is a way to contend with this explosion and organize
people-to-people connections, people-to-machine, and machine-to-machine communications. If
organizations embrace this opportunity to organize these automated communications and leverage all the resulting data at different layers, the visibility and analysis enabled will lead to new levels of
visibility, capabilities, accuracy, and control.

A Smart Machine Controller Appliance would be placed on-premise closer to the machines it controls for any of the following reasons:

(a) The controller function needs high-availability and high-speed connectivity
(b) The controller has large bandwidth requirements for the amount of data that needs to be analyzed and aggregated for immediate feedback back to the running machine process
(c) The controller appliance needs to aggregate data locally during the processing of a machine job 
because the higher level systems do not need to know each little data transaction generated by the 
machine during the job. The higher level MOM functions only need summary data like job start, job end, quantity complete and quantity scrapped. This approach minimizes the requirements on bandwidth due to unnecessary levels of details traveling into the cloud systems.

The requirement for real-time control of machine processes is a very good reason for a local controller appliance. If connectivity is lost between the MOM user and the MOM application for a few minutes, it might be a bit frustrating for the user, but it will not cause a machine process to fail causing loss of invested labor and material for in-process product. The controller appliance would have a cache memory to store a full machine program before it starts a machine run or similar to how video streaming is handled for movies on demand. If connectivity is lost between the MOM application and the controller appliance for a few minutes, the appliance should be able to continue and start transmitting again when the connection is regained.

For example, in industries where the same product is made in large quantities every day for a long
period of time and only summarized information is required at the MOM level, it would be easy to see the MOM functionality hosted in a cloud service. If we only need to know at the MOM level that the machines produced 100,000 units in the current run, it would be wasted network bandwidth and application processing to send 100,000 transactions to the MOM level.

The appliance approach also provides a way to support older machines and controllers in the new Smart Manufacturing systems landscape as newer smarter machines are introduced to the factories. The Smart Machine Controller Appliance would be able to talk “smart” up to the central MOM layer using standards like OAGIS, MIMOSA, ISA88, and ISA95, and talk down to the older machines using protocol standards like OPC UA, MTConnect, EthernetIP CIP, Profinet, Modbus, MQ Telemetry Transport (MQTT).

The distributed layered model also extends into higher systems levels that operate between global
locations, into the supply chain, or into customer systems. There can be a layer of systems on top of
the MOM layer that only needs data aggregated at higher levels. At higher levels of the organizations
and business processes, we might only need work order, or project, or daily numbers. We might not need to know the details of each machine job when we are looking at performance metrics for the
organization.

Smarter machines are coming

As the standards evolve for the IIoT, newer “smarter” machines will enter the factories with the
capabilities of the Smart Machine Controller Appliance already built in. The detailed machine
transactions will be gathered in real-time from intelligent sensors and other monitoring technology
that will provide current machine conditions, the state of the production process in the work cell,
state of automated material handling, and local analysis of data for SPC control, alerts, and
programmed automated self-adjustments. Smart machines might also be equipped with sensors that verify product quality during the production run instead of waiting until the entire run is complete to do manual sampled inspection.

When machines become smarter with on-board controllers and diagnostics, the traditional functions of the SCADA system are handled by a combination of functions at the smart machine and at the MOM layer. For example, a MOM function can provide a view of the manufacturing process status or manufacturing assets’ status on a plant layout diagram.

Apps become smaller and focused

Today’s enterprise systems landscape is full of monolithic software applications that have been loosely interconnected at the database level, operate inconsistently, and are not optimized for any one function. If interoperability standards are embraced for integration of future smart manufacturing systems, not only inside the plant, but among global locations and the supply chain, I can see a future where smaller specialized apps (short for applications) are easy to incorporate into the manufacturing systems landscape. Smaller apps would be optimized for specific functions and specific users and specific hardware platforms (phone, tablet, work station or wall mounted monitor).

References:

• “Lessons Learned From Cloud in Manufacturing Industries”, Hagemeyer, Koslowski, Halpern, Scheibenreif, and Shanler, Gartner, 2014
• “The Evolution of Manufacturing Software Platofrms: Past, Present, Future”, Mark Davidson, LNS Research, 2013
• “The White Book of Cloud Adoption”, Ian Mitchell, Stephen Isherwood, and Marc Silvester, Fujitsu, 2011

 

 

Opportunities Ahead for the Internet of Things in Manufacturing

I just read a very nice Gartner paper by Simon Jacobson titled "Four Best Practices to Manage the Strategic Vision for the Internet of Things (IoT) in  Manufacturing". Good paper. 

There is a potential for convergence of IT (Information Technology) and OT (Operations Technology) in the near horizon as the standards-based IT technologies make their way into the new generation of manufacturing machines and systems. Some of the forces helping this convergence include the growing needs for interorganizational collaboration, a desire to mine more realtime data, the expansion of mobile and wireless technologies, and trends to embrace more bring-your-own-device policies in our plants.

The IoT doesn't have to be on the Internet.
The IoT doesn't have to be on the Internet.

I repeat that twice because I have heard several skeptics discounting the technology opportunity because they don't believe that the plant equipment will ever get direct access to the Internet. However, I am hoping the term used by Simon, "The Intranet of Things", catches on. In the short term, we should focus more on the converge of IT and OT, and less on trying to push data into the
cloud.

Some of the examples of the manufacturing IoT opportunities include:
* Automated kanban replenishment across lines/sites/tiers
* Job prioritization via machine learning and sensors
* Remote monitoring and alerts via personal mobile devices
* Accelerated quality checks via asset connectivity
* Automated equipment configuration based on product RFID recognition

These are just some teaser points from the paper. If you have access to Gartner's manufacturing reports, the full paper is a must read. 

Reference:
Four Best Practices to Manage the Strategic Vision for the Internet of Things in Manufacturing
https://www.gartner.com/doc/2899318

Smart Manufacturing needs a Real-time Integrated Enterprise

The smart manufacturing factory employs 21st century technology to fabricate and assemble a mix of configurable products in response to immediate customer demands. It implements advanced processes that can incorporate technology innovation as fast as scientists and engineers develop it. It marries information, technology and human ingenuity to bring about a rapid revolution in product design, development, manufacturing, distribution, sales and service. It delivers these process improvements while also improving worker safety, minimizing environmental
impact, and improving product quality.

The smart manufacturing factory is at the intersection of a few technology initiatives including the development of smart manufacturing devices that are part of “The Internet of Things” (IoT), 3D model based manufacturing, and a re-architecting of enterprise systems around services and integration standards to improve communication speed and accuracy not only within the organization, but also with the entire partner and supplier network.

Smart Manufacturing Automation Devices

Manufacturing machines are getting smarter and are equipped with their own computers that control and coordinate a myriad of microprocessor chips on every sensor, motor, and actuator. Robots have been working behind fences automating many of the dirty, dangerous and dull work in the factory, and work requiring high levels of precision and consistent repetition. A new generation of easily configured and set up robots are being developed to assist human personnel side by side. For example, a prototype robot named Baxter (by Rethink Robotics, http://www.rethinkrobotics.com/baxter/) is taught his task through a demonstration by the operator on how to move its arm and hands to accomplish the task.

In the past, each advanced manufacturing center was managed as a process island within the plant operated by a few experts with its own special procedures and controls. The new generation of smart manufacturing equipment connects to the wireless network as easily as our cell phones and
computerized glasses (wearable technology in general), and will be ready to receive input and broadcast feedback. This creates an opportunity to standardize on new equipment and application data exchanges—machine-2-machine (M2M) and machine-2-application (M2A) —that eliminate the information silos within the plant.

For example, our espresso machines can already broadcast when they need coffee beans and when they need to be cleaned via a display at the machine. What if the machine also broadcasted that information to our home computer? An application on our computer could be tracking the inventory level of coffee in the pantry, the weekly usage pattern from our coffee machine, and could use this information to forecast when we would run out of coffee and even automatically put coffee on our shopping list. These are some of the promised concepts at home from the “Internet of Things” (IoT) (http://www.iot-a.eu/).

IoT concepts extend to the factory floor and the next generation of smart machines. There are efforts for a Common Industrial Protocol (CIP) to facilitate these type of data exchanges in the factory between machines, computers and personal devices.

The German government refers to this next generation of connected manufacturing machines, robots and information systems as “Industry 4.0” (http://www.bmbf.de/en/19955.php) and looks at it as the fourth industrial revolution. But to make Industry 4.0 a reality, equipment manufacturers will need to embed intelligence and communication capabilities into their products and we will need broadly accepted standards for communicating, collecting data and interacting with the equipment.

In the United States, NIST’s Smart Manufacturing Operations Planning and Control Program (http://www.nist.gov/el/msid/syseng/smopc.cfm) aims to enhance U.S. innovation and industrial competitiveness by facilitating the adoption of smart manufacturing systems (fully-integrated, collaborative manufacturing systems that respond in real time to meet changing demands and conditions in the factory, in the supply network, and in customer needs). This program will enable smart manufacturing based on efficient networked sensing and control, prognostics and health management (including diagnostics and maintenance), integrated wireless platforms, industrial control security, efficient information exchange and interoperability of system components.

Real-time Integrated Processes and Information Systems

IoT deployments will generate large quantities of data that need to be processed and analyzed as close to real time as possible. If a system can’t keep up with the volume of data, it will increasingly fall behind and its analysis and processing of old data will quickly be obsolete and of no value.

The recent trends in enterprise information technology (IT) have been to centralize applications to reduce costs. However, organizations will need to rethink that IT strategy or risk creating a bottleneck in an IoT world. The processing of data streams from smart devices will need to be
distributed and layers of systems will aggregate and filter the data from lower level systems close to machines, to layers of systems managing business processes (internally and into the supply chain) and all the way up to enterprise systems with centralized financial information for the business.

This might sound similar to having a SCADA or historian system collect machine information and pass filtered and aggregate data up to a Manufacturing Operations Management (MOM) or ERP system, but it is different because the smart machines can do much more processing and
filtering of the data themselves and will be communicating with the same protocols that our cell phones and TVs use. For these smarter devices, we can probably skip the traditional layers 0-2 in the old ISA95 and ISA88 models. The machines might broadcast straight to a cloud service which in turn can broadcast to our personal device which has been registered via the company’s portal to receive specific types of messages.

From the product design side, especially in Aerospace and Defense industry, the “Model-Based Enterprise” (MBE) (http://model-based-enterprise.org/) is redefining how manufacturers work with engineering and suppliers in the digital 3D world. Product definitions in 3D formats need to be communicated through the supply chain and through our own internal systems for procurement, production and quality control. Change management practices in the 3D world set the bar higher than what could ever be achieved via 2D drawings and paper forms. The goal is full associativity between engineering, inspection, manufacturing, and service definitions to facilitate change and configuration management practices among multiple tiers in the supply chain.

NIST has a digital thread for Smart Manufacturing that picks up the work from MBE and takes it downstream and links it to the Smart Manufacturing infrastructure (http://www.manufacturing.gov/docs/DMDI_overview.pdf)

Over 50% of the actual manufacturing of a product happens in the supply chain and over 50% of the data exchanged with partners and suppliers still travels today over email, phone and fax rather than flowing directly between business applications via B2B (business-2-business) integration in
structured XML. This low adoption level of B2B integration is surprising given that the first EDI systems were introduced four decades ago and XML standards have been around for decades also. There has been a lack of a concerted effort to tackle this integration arena. Perhaps because
organizations have been plenty busy trying to orchestrate A2A (application-2-application) integrations within their four walls. However, with such a big percent of the success of the company riding on the reliability of these communications, it is time to start improving B2B
integration techniques with our supplier network. 

MESA (http://www.mesa.org) and the Open Applications Group (OAGi, http://www.oagi.org/) have recently signed a collaboration agreement. OAGi is a standards organization managing XML integration standards for A2A and B2B communications and is widely used in the discrete manufacturing arena.

APICS has recently joined with the Supply Chain Council (https://www.gartner.com/doc/2728128/supply-chain-councilapics-merger- help) and they have the SCOR framework for supply chain management.

The SCOR model addresses business practices but do not translate to B2B integration requirements. OAGi is working on mapping SCOR to B2B integration standards. NIST is also working with OAGi on integration standards that span into the supply chain.

Manufacturing organizations that want to lead the next generation of supply chain communications should join these organizations and participate in these efforts.

Benefits of a new real-time integrated enterprise platform for smart manufacturing include:
• Accelerate time to market for innovative products
• Future-proof the IT investment with flexibility to easily switch best-in-class functional modules
• Reduce total cost of ownership with simplified management across the platform by leveraging plug and play integration
• Ensure tight integration between enterprise applications and operational systems at the shop floor
• Increase speed and accuracy throughout the extended value chain
• Gain insight you can act on with metrics acquired directly from transacting the business process model

 

 

Are We Keeping Our Machines Happy?

I love this story. "What happens if Voyager runs into a planet? Who will fix it if it breaks down?"A five-year-old boy has questions for Astronaut Cmdr Chris Hadfield. He was worried about the Voyager alone in space.

 

 

 

Audio: http://www.cbc.ca/player/News/Canada/Audio/ID/2530849070/

Makes me wonder if we are keeping the machines at the shop floor busy and happy? What about the next generation of smart machines and robots? Will they be happy? Will we be as interested in our smart machines as the boy with Voyager?

Moving forward with Manufacturing Apprenticeship Programs

Tognum, a Germany company with factories in South Carolina, moves forward with apprenticeship programs modeled after the ones in Germany in partnership between manufacturing companies, goverment and academia.

More of these programs are needed to fill the manufacturing skills gap as manufacturing companies start growing again and continue reshoring operations.

Read full article here:

http://mobile.nytimes.com/2013/12/01/business/where-factory-apprenticeship-is-latest-model-from-germany.html?_r=0&goback=%2Egde_3758755_member_5815870119015890947