Manufacturing Operations Management Talk

Top Seven Manufacturing Challenges in 2020

We have been hearing about the promised value of Industry 4.0 for several years. 85% of businesses agree on this potential. However, manufacturing productivity has been flat for the last decade and many industry digital initiatives are stalled. Many manufacturers have not started initiatives and many others are in assessment mode with a few pilot projects.

Some of the challenges for manufacturers are new:

#1. Uncertain demand rebound for some goods

Although manufacturing is not on the top five on the list of impacted industry jobs during this pandemic, it is still showing a big impact at number six on the list. However, it is not a question of whether it will bounce back or not, it is more a question of when and how fast. We hope manufacturing will be one of the sectors to bounce back quickly from the impact of the pandemic.

#2. Higher productivity is needed to reshore

One of the encouraging trends is reshoring. There are several reasons for the shift from offshoring to reshoring. Economies in many go-to offshoring countries have grown stronger, resulting in increased wages for their residents. In the locations where labor is still inexpensive, the infrastructures often cannot handle complex manufacturing operations. Industry is also looking to reshore suppliers in critical medical and food supply chains where reliance on imports surfaced big issues during this pandemic.

To sustain the reshoring trend, manufacturers must continue achieving increases in productivity using new technologies like smart manufacturing and robotics to automate many of the processes that used to require intense human labor. All in all, this resurgence in reshoring will lead to an increase in made in the U.S.A products in the future.

But prior challenges for manufacturers are still there:

 #3. Global competitive pressures

The U.S. is no longer on the top of the list of manufacturing most competitive countries when you consider innovation capability, health, skills and business environment. What will it take for U.S. companies to reclaim and hold the top spot? Manufacturers will have to shift their focus to advanced technologies and smarter talent for greater competitiveness.

Shifts in sourcing and shipping logistics are constantly evolving throughout the manufacturing industry, especially as a result of the COVID-19 pandemic. The ongoing trade war between China and the U.S. rages on, causing the short-term outlook for domestic companies to be uncertain. Manufacturing supply chains will need to be more resilient in adapting to potential future disruptions.

Manufacturers should focus on delivering the best digital customer service experience possible and increase their efforts toward digital projects that build agility and scalability to help to manage risk in supply chains during disrupted and uncertain times.

#4. Exponential pace of technology innovation   

From sensors, to automation, artificial intelligence, robotics and cloud computing, the challenge for many manufacturing companies is keeping up with the rapid pace of technology innovation. Not only to use it in their products but also to leverage it in their processes and customer services.

Newer industrial automation equipment incorporates sensors, controllers, computers, and network connectors. The use of robotics including robots working alongside humans is expected to triple or quadruple the next five years. Yet, integration of equipment to manufacturing systems is still too expensive for many small and medium manufacturers.

Many manufacturers understand the important role technology plays, yet many also feel they are not providing their team the best tools for bottom-line success. Thus, there is often a disconnect between understanding the need for new technology and actual implementation and adoption.

#5. Increasing complexity in products and supply chain

Over the last years most manufacturers have seen their products become more complex. Not only are products increasing in complexity, but many organizations are not equipped with the right tools to manage the intricacies of complex product development and manufacturing.

Product designs are getting more intricate with new materials, more parts and an increasing number of electronic components, microprocessors and embedded software. Not only are the number of components increasing, parts are sourced from multiple vendors and are now much smaller and more technologically advanced, adding another layer of complexity to the product and its manufacturing.

Organizations need information systems to help with these complexities in the product lifecycle starting with design, through supply chain and manufacturing operations. Modern supply chains are dynamic with a lot of change taking place, a lot of stakeholders involved, and increasing requirements for data exchange for higher collaboration, transparency and risk management.  

#6. Talent pool shrinking for manufacturers

During the past several years, the skills gap has been top of mind for U.S. manufacturers. We can forecast that the demand for talent in manufacturing will come back in the next few years, due to retiring baby boomers and reshoring trends. Many manufacturing jobs were going unfilled over the past few years and that trend will probably pick up again once manufacturing starts hiring again.

Even in an age of automation and robotics, skilled workers are still needed for their problem-solving capabilities, to fill managerial positions and to perform analysis. Baby Boomers are aging and retiring and there are simply not enough skilled workers to fill the positions they’re leaving. To fill the widening skills gap, manufacturers will need to train existing workers to perform skilled tasks and get creative in their efforts to attract workers.

#7. Bombarded by vendor’s varied propositions

In an ever-accelerating digital era, businesses feel pressured to meet rapidly changing customer demands, reinvent or evolve themselves, and beat competitors to the punch by being the first to provide faster and better solutions. To thrive in this new data-rich era, manufacturers want to adopt new technology at the plant floor and mine their data into smart software systems to continuously monitor, analyze and optimize the use resources in their complex operations.

However, there are many technology options to evaluate and many vendors putting forward great sounding value propositions for big data, artificial intelligence, IoT platforms, workflow tools, PLM, ERP, MES, QMS, EAM, and supply chain management systems. In the quest to reap the benefits of these technologies, organizations may focus too heavily on the hype surrounding specific technologies, as opposed to whether the innovation can help solve their problem or business strategy.

It is essential that organizations put a good plan together that focuses on achieving business goals, adapting to marketplace changes, and taking significant steps towards achieving their long-term Smart Manufacturing vision.

Conquering the barriers holding back adoption of Smart Manufacturing technology could create a competitive advantage, while simultaneously helping to battle competition from overseas and the manufacturing skills gap. In future articles we will discuss strategies for conquering these challenges.

Six Trends Accelerating the Smart Manufacturing Future

The Smart Manufacturing future is upon us with intelligent, real-time orchestration and optimization of business, physical and digital processes within factories and across the entire value chain that delivers the end-product. A value chain wherein resources and processes are automated, integrated, monitored, and continuously evaluated based on high levels of transparency and data exchange as close to real-time as possible.

A vision for Smart Manufacturing within reach in the next two decades thanks to advances in platforms that are making integrated systems and technologies accessible to more manufacturers, and further empowered by consortia focused on making available the knowledge required to run Smart Manufacturing systems and ecosystems.   

Several trends are fueling optimism on achieving the Smart Manufacturing vision:

#1. Product manufacturing and service are converging based on new market demands

For many products, the market is switching from buying a mass-produced product off-the-shelf to buying a custom configured product as-a-service. These new blended manufacturing-service business models require more customer interaction and elevate the value of the digital data that goes along with the product during its service life. These ecosystems are forced to evolve to deliver the required data services.

#2. Manufacturers are redefining their processes and services around new enabling technologies

New technologies are not just enabling optimization of existing processes, companies are rethinking their processes, value chains, and business models. The proliferation of smart phones, Internet of Things (IoT), cloud services, low-code platforms, and DIY machine connectivity are causing manufacturers to empower the customer and internal citizen technologist (engineer, developer and data scientist) with more data and tools in order to accelerate the pace of innovation in the whole ecosystem.

#3. Hybrid human-machine processes are on the rise

About three decades ago, when innovation led to the high use of robotics in factories, many people predicted that within 10 years all factories would be filled with robots, and there would be no human operators. Decades later, more than half of the manufacturing tasks are performed by human operators.

Rather than replace humans, robots will work collaboratively with a balanced distribution of responsibility. Technologies like cobots, exoskeletons, artificial intelligence (AI), and augmented reality (AR) will augment, assist and empower the future worker.

#4. Manufacturing ecosystems are achieving higher levels of connectivity and transparency

There has been much progress in engineering, production automation, and enterprise business systems in the last few decades within their respective islands. Manufacturing operations Management (MOM) systems and paperless operations are the new norm in the factory. Machines are getting smarter with embedded computers, AI, and application program interfaces (APIs) ready to exchange data with MES and cloud platforms. Smart Manufacturing eliminates manual steps and inconsistencies bringing silos of information together and finally links them in a full digital thread of automated data exchanges.  

The smart factory becomes a node in a connected smart ecosystem with API requirements for partner and customer interaction. The required data exchanges go beyond purchase order, shipment and warranty data if the ecosystem is delivering new data services with the product. For example, if a company is including a product digital twin as an additional service, it must be ready to make accessible, to the ecosystem and customer, 3D and simulation models of the product along with each unit’s unique as-built and operational data.  

#5. Manufacturing systems are incorporating more automated intelligence 

The availability of low-cost sensing, pervasive connectivity and cloud computing services has made it practical to access and holistically analyze data across integrated systems. Unstructured datasets such as images, natural language, and even messages in social media have become part of the data available for analysis.  More integrated data and AI capabilities are bringing us closer to systems with automated routine decisions where humans intervene only when necessary.

#6. Manufacturing culture is embracing digital

Manufacturing companies are investing more into their organizational culture. There is a recognition that technology plays a key role in the company image and in attracting talent.  National governments have incentives for companies to adopt Smart Manufacturing and are supporting efforts to educate the workforce with the required new skills.  Staffing services are evolving to fill the demand for highly specialized skills.  

 

 

Smart Manufacturing Feud Verifies MOM and Digital Twin Popularity

MESA had a recent web event focused on Smart Manufacturing with a game show type of format and an opportunity for the audience to participate through polls. The Smart Manufacturing Community Feud was initially inspired on the Family Feud game show, but the idea was modified to an interactive format with the webcast viewers.

Two topics are worth highlighting because they do not conform to some of the industry analyst opinions.

• When asked about Manufacturing Operations Management (MOM/MES), the popular opinion is that MOM is evolving as a central repository of contextualized data. However, many also believe it will also be divided up into smaller modular apps. These are not mutually exclusive options. The MES platform can be designed to provide the data layer separately and allow varied modular apps to interact with the data layers via APIs.
• The most surprising response was the excitement around digital twins. There is a significant percent counting on the results of digital twin initiatives as an essential part of their business model. However, there is concern about the investment required and the effort to align multiple parallel initiatives among different departments working on simulation models and digital twin type of functionality. 

Other key points from the discussion are summarized below. These echoed many of the opinions we have received at workshops and regular calls with the MESA Smart Manufacturing Community members.  

• There is still a big percentage of manufacturers that have not fully embraced the Smart Manufacturing journey, but the industry leaders are starting to share their success stories and initiatives are becoming more prevalent.
• However, over half of the companies polled reported a mismatch between their Smart Manufacturing goals and the vision portrayed at conferences. Many have set their expectations for Smart Manufacturing much lower.  This aligns with previous surveys where there seems to be a 50-50% split on people focused on cost reduction and optimization versus business transformation and new business models.
• The vast majority believe that workers will be part of the factory of the future, but they will be augmented by co-bots, exoskeletons, and AI-driven assistants.
• Most agree that we do not need more data than we are collecting today. Having data does not seem to be the problem. We are either not collecting the right data, or we are not organizing, relating and modeling the existing data in ways that enable better use of analytical tools.
• Many are expecting security and privacy standards to evolve quickly and become the new norm in the industry for the entire supply chain. There is also enthusiasm behind blockchain as a technology that can help with data exchanges among value chain partners.

The link to the full recording is available at:

The Smart Manufacturing Community Feud – Episode 1  

https://services.mesa.org/ResourceLibrary/ShowResource/a65664c2-eeb1-4dcd-9075-dbc7d69d008c

This Industry 4.0 Revolution is Very Different – It’s About Ecosystem Transformation

I experienced the end of the Third Industrial Revolution as I began my career in manufacturing. Closed government and private networks gave way to an open network called the Internet. Numerical Controlled (NC) machines, Programmable Logic Controllers (PLC), and Personal Computers (PCs) were adopted at the factory floor. They were integrated to automation and tracking systems based on spreadsheets and the first wave of commercial manufacturing software, Computer-Integrated Manufacturing (CIM), which became the Manufacturing Execution System (MES).

We are now amid the Fourth Industrial Revolution. It is fueled by the convergence and proliferation of multiple game-changing technologies. including smart phones, cloud computing, 3D simulation, 3D printing, robotics, augmented reality and AI—coupled with advances in speed, capacity and affordability of computers, networks, sensors and integration platforms that enable enhanced platforms for commerce and industrial systems.

Where the last revolution felt focused on productivity gains through mass production and optimization of the factory, the current revolution feels focused on a new era of manufacturing supporting mass customization and products sold as services. It is finally possible to move forward with initiatives that started decades ago, about automation, data acquisition and bridging the IT (information technology like MES) and the OT (operational technology like PLCs) across many vendors and standards. However, many management teams are looking beyond the optimization and continuous-improvement mode of the last few decades.

The story behind this revolution is much bigger, and it is focused on transformation to new business models, orchestration of the value chain and evolving manufacturing ecosystems. Ecosystems with a mix of firms making parts and machines, developing software and providing services along with products. Separately, each ecosystem participant can focus and become very efficient in specialized competencies. Together, ecosystem partners can deliver complex solutions to the customer with a high level of customized service.

It is generally accepted that a great many business executives believe ecosystems are important—and that many are still unable to balance between investing in optimization of the current business and exploring the opportunities of new ecosystems and business models.

To get ready to participate in evolving ecosystems, start by making sure a digital backbone is established within each factory. A manufacturer still running the plant on paper will not be ready for a digital ecosystem. Every machine might not need to be connected to the factory system, but data-intensive stations placing a lot of components, running complex programs and inspecting parts should be providing data directly into a manufacturing system like MES. Every physical job needs a digital footprint in the MES. The MES is managing production and quality-control processes while updating in real time the production and customer orders in integrated enterprise systems like ERP with information that must eventually flow directly into the ecosystem network.

Technologies like data-integration hubs and IIoT platforms are facilitating the infrastructure. But establishing an efficient digital value chain and ecosystem is a complex issue for individual firms to tackle. Organizations must start thinking about the data and APIs needed for bi-directional communications among ecosystem participants and create a roadmap for how and when internal systems will support those types of data exchanges.

The journey to a connected ecosystem will take a few years with work to be done outside the four walls of the company. Industry groups, consortia, and institutes like MESA International, IIC, CESMII, and NIST are helping facilitate the convergence to digital infrastructure and data-exchange standards required to democratize the participation in ecosystems.

But many firms are sitting back and waiting. A far better move is to engage with these organizations now.

 

This article was published as: Ways to get ready to take part in evolving ecosystems, SME.org, C. Leiva, 2019

https://www.sme.org/technologies/articles/2019/october/ways-to-get-ready-to-take-part-in-evolving-ecosystems/

 

Taking Evolutionary Steps Towards Smart Manufacturing

In a recent article we discussed the hidden treasures within manufacturers’ existing systems. If the organization has already taken steps to go paperless and get the most out of existing systems, what do they work on next?

We tend to use the term digital transformation when we talk about Smart Manufacturing, but the term digital evolution might be more appropriate to describe the journey. We do not want to imply that this is a rip-and-replace all systems proposal. Many companies have already begun the transformation and have systems in place like a Manufacturing Operations Management (MOM), Manufacturing Execution System (MES), PLM and ERP that are important foundational linchpins. For these companies an integrate-and-extend strategy is more appropriate.

Leverage existing systems

Organizations can leverage the advances they have made in recent years. Extending and integrating existing systems can help mitigate risk and save money.

A recent survey from Gartner [1] and MESA International reveals that 98% of manufacturers believe there is more value to capture from their current manufacturing system and have identified next steps to extend and further integrate systems in their digital evolution journey.

Manufacturers have identified the following areas as small evolutionary steps towards the Smart Manufacturing goals:

Mine and join data across silos

Manufacturers have more data on-hand than they realize. Existing data might be trapped in silos or not organized to enable joining data across systems. For example, MES data is usually leveraged for operational metrics but could also be made available to join with data in other enterprise systems like ERP and PLM for higher levels of business analysis and optimization.

Industrial IoT (IIoT) platforms are capturing data straight out of sensors and smart machines for predictive analysis tied to equipment maintenance. This data could also be joined to MES for more automated and accurate real-time data collection.

Integrate via APIs

Application Programming Interfaces (APIs) can not only facilitate integration into a system of systems, but also expose data for mining across the enterprise.

API strategies that extend into the supply chain uncover a substantial amount of valuable data. This is because most supply chain visibility applications concentrate on connecting plan, source, make and deliver domains, and rely on ex-post-facto production data. In turn, most manufacturing enterprise applications provide real-time data and analytical tools focused solely on internal plant optimization and asset performance. Integration of these systems would provide better orchestration and optimization opportunities for the plan-to-produce and order-to-cash processes.

Analyze with AI

Artificial intelligence (AI) and robotic processes are helping manufacturers sense, extract, synthesize and analyze data across traditional silos. Not just across internal systems, but also across partners, suppliers and customers. AI can make it practical to organize these varied data sources into meaningful insights to fulfill the higher analytical and optimization goals of the Smart Manufacturing integrated enterprise.

References

[1] Survey Analysis: More MES Value to Be Captured from Supply Chain Collaboration and IIoT, Franzosa and Jacobson, Gartner, 2019

Hidden Treasures In Plain Sight - at the Manufacturer’s Shelf

There are hidden treasures at the manufacturer’s shelf and we are not talking about the inventory shelf. We are talking in this article about the IT shelf of already owned software that is not being used. More specifically about the Manufacturing Operations Management (MOM) or Manufacturing Execution System (MES) software the company purchased a few years back and hasn’t been deployed to its full capabilities.

Gartner has recently published some interesting survey results validating this premise. [1] Figure 1 shows that even though most companies have achieved the expected return on investment (ROI), they still believe that there is more value to capture with their MES.  

It seems that it is easy to achieve the initial benefits and then move attention to other things. Does management even know about these potential benefits? Has the organization bothered to present these additional areas of improvement as possible phase 2 or phase 3 projects with their own ROI?

I have seen these types of stories often. The next steps are perceived as harder work. We took care of the “low hanging fruit” in that first phase but the next phase is going to take harder integration work. However, the potential benefits can also be much bigger.

In fact, MES is a foundational enabler to the Smart Manufacturing strategy and it was probably not positioned that way in its first implementation. MES is often implemented and justified based on the benefits of eliminating paper-based processes in production. However, as illustrated in Figure 2, Gartner has documented that companies that fully embrace the MES as an enabler to more process improvement and business transformation are achieving three to ten times the initial benefit in the next three to five years. [2]

The fact that the MES is not fully rolled out to all facilities and programs might be obvious, but the fact that there is more functionality and integration potential left on the table might be a little less obvious.

Typical areas of process improvement post initial implementation of the MES include:

• Integration of in-process quality management processes, material review board (MRB), rework specifications, and corrective action management.
• Integration of automated factory equipment like parts placement and inspection equipment that collected a lot of data that could be pumped directly into the MES.
• Integration of engineering data directly from the PLM system including 3D CAD as the basis for 3D visuals for work instructions and integration of specifications in PMI directly into the MES inspection verification requirements.
• Integration of the supply chain management processes including supplier quality management.

If your company has forgotten to pursue these opportunities, you are not alone. But the good news is that you have already done the hard work of implementing phase one of the MES. It is time to fully leverage that initial investment and start planning the next phase of MES at your organization.

If you have access to MESA International or Gartner research papers, I encourage you to read these reports for more insights on how to get the most value out of your MES investment.

References

[1] Survey Analysis: More MES Value to Be Captured from Supply Chain Collaboration and IIoT, Franzosa and Jacobson, Gartner, 2019

[2] Get the Most Out of Digital Manufacturing by Extending the Value of Your Manufacturing Execution System, Franzosa, Gartner, 2016

 

 

Manufacturing Operations Management Takes Center Stage for Industry 4

Many new technologies are being introduced these days into manufacturing, yet the Manufacturing Operations Management (MOM) or Manufacturing Execution Systems (MES)—which has been around for decades—is viewed as a fundamental enabler for the Smart Manufacturing and Industry 4.0 digital transformation. Technologies like augmented reality, artificial intelligence, cloud and edge computing, mobile, and auto-ID are being integrated into MOM solutions. Likewise, smart machines, sensors, and IIoT platforms are expanding capabilities to integrate to enterprise systems like MOM.

Regardless of rumors about the potential demise of MOM solutions, the facts are that many of the functions and features provided by MOM cannot be replaced by new IIoT platforms, even with analytics and apps. Alone, IIoT devices and platforms do not offer many new possibilities to manufacturers because they cannot provide operational context for data, cannot trigger actions in response to data, and are not designed to orchestrate processes across the factory and value chain. Many production processes need the human in the loop and MOM provides that platform.

MOM does not deliver Smart Manufacturing by itself. It needs to be integrated into the organization’s digital platform and “system of systems” including engineering, business, and automation systems. MOM does provide these important features required to integrate Operations into the Industry 4.0 digital transformation strategy:

• Intelligent Insights.Raw data captured from machines and workers during production must be turned into information by adding context and organization. Context includes data about the product specifications, process step, people, and equipment involved in the activity when the datum—like a dimensional measurement or environmental condition—is captured. Organization of stored data is also important to enable views that joins data from multiple activities for correlation and root-cause analysis. The organization of data makes it easier to aggregate data into significant metrics and key performance indicators (KPIs). It helps put the human in the loop to make better decisions quickly. 
• Data Stewardship and Governance.A proliferation of custom apps in production can lead to a multitude of data silos that are not coordinated to facilitate integration and aggregation. The MOM database provides de-facto governance, through its production-centric data model and integration interfaces, maintaining data clean, normalized, and organized to facilitate joins and searches across data in the enterprise.
• Standardization and Control. The MOM manages and enforces every aspect of the work steps including equipment, materials, and data collection for automated and manual processes. MOM enforces the policies and rules to make sure people and equipment are operating as they’re supposed to. The standardization makes production processes repeatable with consistent performance and quality.
• Response Action. MOM functions include methods to handle exception-driven events during the production process. Events or incidents like a suspect defect or process anomaly. MOM is the natural system to receive these types of notifications and alerts from an IIoT analytical platform. In MOM, these triggers can initiate procedures to record a discrepancy, change the equipment settings or operator instructions based on an automatically detected condition.
• Connection and Digital Thread. MOM provides an integration bridge between the plant and key enterprise systems including engineering’s PLM system, and procurement, inventory and cost management’s ERP system. This integration can be orchestrated to provide a digital thread linking the product’s engineering design specification to the product’s realization process, and even the product’s sustainment services in a way that facilitates the maintenance of a digital twin for each physical product unit.  The digital thread and digital twin can provide many benefits including better data exchange across the enterprise, and capability to analyze the product design against actual performance for continuous improvement. The digital thread accelerates the introduction of new products and variations by making it easier to implement design changes into downstream production definition elements like inspection requirements, machining programs, and work instructions.

The need for more real-time factory data and enterprise-wide connectivity is refueling the interest in MOM and MES. IIoT technologies are a great addition to the manufacturing IT landscape however, for the reasons listed above, MOM is needed more than ever as a foundational piece to the Smart Manufacturing and Industry 4.0 strategy.