Manufacturing Operations Management Talk

MOM Cures Three Legacy Ailments in Operations

Manufacturers are picking up the pace of new product introductions to satisfy the customer demand for products that incorporate the latest technology innovations. The need for faster innovation adoption into product lines fuels a need for more efficient change management procedures throughout the organization. Many are asking themselves, "Is it possible to handle higher levels of product and process change with small patches to old practices?" Probably not. Strategic level process improvements are needed to increase the capability of the organization to handle higher rates of product updates and new product introduction.

Engineers are using the latest CAD technology to make better, more accurate,  3D models faster leveraging reusable components. 3D models include more product and manufacturing information (PMI) for use downstream in Model-Based Manufacturing, to simulate and accelerate production process innovation, in Manufacturing Operations Management (MOM) to develop shop floor for work instructions, and create automated inspection and test procedures. So why are some organizations still working with 2D drawings, spreadsheets, and paper work instructions at the shop floor? We have found three ailments that hold back many organizations from significant improvement in their change management speed and we have one prescription that helps all three.

Significant strategic process re-engineering can only happen when organizations face head on the following ailments brought upon the organization by a legacy of paper-based practices.

Dependence on Manual Processes is Holding Manufacturers Back

With the technology available today, any manufacturing organization should not be relying on paper-based or spreadsheet-based processes at the shop floor to collect data, track progress, and prepare product or service documents for the customer. Yet many companies still depend on paper today. 

Even traditional Lean Manufacturing practitioners like Toyota are embracing information technology to raise the organization’s performance to a new level. Toyota US CIO, Tim Platt, spoke about "Lean's High Tech Makeover" [1] at the 2014 Industry Week conference. If an organization like Toyota can move beyond the manual Lean processes they promoted for years, other organizations can change too and embrace automated Lean processes supported by information technology.

With a manufacturing operations management (MOM) system the organization moves into a completely paperless system for managing operations. Before MOM, operations would work on piles of paper work orders filled and assembled manually into massive build books. Many labor hours wasted on moving paper, organizing paper, fixing missing information and mistakes. When work orders, instructions and records are digital the paper handling waste is eliminated and processes are hugely streamlined. The mechanic does not have to search through paper or online drawings or books to find the information he needs. The online work instructions will have quick shortcuts and links to documents

Poorly Defined Business Processes are Hiding Inefficiency

It is very difficult to see opportunities for improvement without a good understanding of current business processes. The implementation of a MOM system forces the organization to a better understanding of the as-is and to-be business processes. Many times these processes are not documented and very few employees understand the overall value chain across the organization. Value stream mapping exercises across functional departments like engineering, production, and quality can be very eye opening. Departments are usually focused on their daily routines and do not spend much time thinking about how their work is affecting downstream activities.

Even if procedures are defined in a book it is often difficult to enforce policies at the shop floor. A MOM system installs a work, documentation and change management discipline on operations. It is much easier to implement best practices.

Inaccurate Delayed Information Leads to Sub-optimal Decisions

In order to make good decisions, management needs good data. It is important to know that products are delivered on time and bills are paid, but management also needs to know details about engineering and production to improve those processes. Data is needed beyond delivered product quality, inspection results and defect counts, details are needed about defect and cause classification to tackle the root cause of problems.

Without the proper data, it is difficult to do proper root-cause analysis and easy to always end up finding someone to blame for the problem instead of finding the true system weakness. In order to go beyond the typical blames of: (a) lack of training, (b) personnel carelessness, and (c) human error, organizations need data that will point to any of the potential resource causing problems including personnel, equipment, processes or product design. Information maintained manually in different departmental databases or spreadsheets (information silos) is likely not consistent and possibly leading to different conclusions and priorities in different departments.

With MOM, real-time dashboards provide status of in-process work access to quality data on any work order with the single press of a button. Quality management can be more proactive, focusing on process improvement instead of focusing on manual documentation. There is complete visibility and accountability of who is performing each task, what resources are causing constraints, and the level of engineering changes impacting operations. MOM systems can also provide manufacturing intelligence and scorecards capabilities to monitor the organization’s achievement of performance goals and help quickly identify areas for improvement.

In Summary

Strategic investments in new information technology and new business processes can look like big cultural and budget challenges, but strategic investments can also lead to big contract wins, big margin gains, and the development of new agile, flexible and lean production operation.

A MOM system helps to eliminate some legacy ailments in operations by providing (a) a platform for agile paperless business processes, (b) a systematic control of manufacturing business practices, and (c) an accurate real-time information system for better performance and continuous improvement management.

References

[1] “Toyota’s Lean High-Tech Makeover”, a presentation by Tim Platt, VP Information Systems, Toyota US, May 2014  

 

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

 

Clarifying the New Manufacturing IT Lingo

- Smart Manufacturing vs Industrie 4 vs Digital Manufacturing vs IIoT

I had the pleasure of facilitating a workshop on Smart Manufacturing at the Industry Week conference with over 120 professionals involved in different aspects of manufacturing information technology (IT) in a wide range of industries. After we briefly introduced Smart Manufacturing and shared a few results from a MESA-SCMWorld survey, I casually surveyed the group on clarity
among the new terms in manufacturing IT and adoption for the “plug and play” paradigms promoted by Industrial Internet of Things (IIoT), Smart Manufacturing, Digital Manufacturing, and Industrie 4.0 initiatives. Some of my observations from this interesting discussion follow.

QUESTION: Third or Fourth Industrial Revolution?

SURVEY SAYS: 4TH Industrial Revolution. The audience was pretty confident with this response. There was an overwhelming show of hands in favor of 4th versus 3rd.

Some consulting groups have favored calling this era the start of the third industrial revolution and others are calling it the fourth industrial revolution. Everyone agrees that the era of mass production is behind us. An era that was enabled by revolutionary advances like the assembly line and electrical standards. But many groups closer to manufacturing automation want to recognize that there was a third industrial revolution that started in the 1970’s fueled by advances in industrial automation and software for personal computers (PCs).

There is agreement that the next industrial revolution is starting now, and it is fueled by advances in model-based manufacturing, additive manufacturing, robotics, and the Internet of Things (IoT). New technologies are allowing manufacturers to move from mass production make-to-stock practices towards make-to-order mass customization business models. Based on popular opinion, we should stick to calling this the 4th Industrial Revolution.

QUESTION: IoT and IIoT side by side or one under the other?

Do we view the Industrial Internet of Things (IIoT) as a subset of the Internet of Things (IoT) with similar standards and methods of connecting manufacturing, home and office devices to cloud applications and smart phones? Or do we see IoT and IIoT as having similar goals but using different standards and infrastructure?

SURVEY SAYS: IIoT should be subset of IoT. The majority of manufacturers want to see industrial automation use similar standards and mechanism to home and office equipment integration. They would like to see apps on their phones with the ability to view, interact and control the shop just like they have apps today controlling their home or car. IIoT standards and methods should be a subset of IoT methods and standards.

One automation vendor warned that this view of IIoT and IoT might be an oversimplified view on the subject. Point taken, but the survey was more about confirming the expectations of these initiatives and the desires of the end users—similar type of “plug and play” capabilities at the factory and at home.

Another voice wanted to claim that many companies are already doing IIoT at their plants. We went ahead and tested this claim with the audience.

QUESTION: How many companies in this audience currently have integration from
machines to enterprise systems?

SURVEY SAYS: Around 80% of hands were up.

QUESTION: How many of these companies are using open standards for integration
and could simply swap out one automation or software vendor for another?

SURVEY SAYS: Only one timid person in the audience raised their hand half way
up.

These answers point to a big difference between IIoT and prior manufacturing automation integration methods. For the last few decades we depended on custom integration, proprietary interfaces and separate protocols for integration and automation at the factory. Moving forward with IIoT we want to embrace open standards and internet protocols so we can easily swap and mix multi-vendor equipment and software which might be on-premise or in the cloud.

QUESTION: Are Smart Manufacturing and Industrie 4.0 the same thing?

SURVEY SAYS: Yes. The consensus was that in general they are close enough in scope and purpose. However, Industrie 4.0 is perceived as a very specific German initiative so the majority of participants preferred the term Smart Manufacturing.

It is important to note that if initiatives from different countries do not coordinate among each other, we could end up with different standards supported by different countries. Similar to how we ended up with slightly different electrical standards in different countries. Nevertheless, better off with a few standards than none at all and we can always use converters to plug equipment to
different standards.

I noticed that the general voting participation was lower on this topic so I paused the survey for a few clarifications.

QUESTION: Would you like more clarification on the scope of Smart Manufacturing?

SURVEY SAYS: Yes.

Smart Manufacturing is about creating smart products, smart factories, smart manufacturing processes and smart enterprise procedures that link the entire product value chain with a digital thread.

Smart factories are the foundation of Smart Manufacturing. Smart machines and robots in smart factories are capable of managing complexity, are less prone to disruption and are able to manufacture goods more efficiently. In the smart factory, human beings, machines and resources communicate with each other as naturally as in a social network.

Smart products know about their configuration, details of how they were manufactured including critical components and how they are intended to be used. They actively support the anufacturing process, answering questions such as “which parameters should be used to process me?”, “when was I made?”, “for which customer?”, and “when do I need to be serviced?”

QUESTION: Should we view Digital Manufacturing as part of Smart Manufacturing or should we view Digital and Smart as separate initiatives?

SURVEY SAYS: Not clear. So instead we further discussed the difference and relationship between smart and digital manufacturing.

The digital thread that starts with the 3D model-based definition of the product from engineering flows to smart manufacturing and to the smart supply chain linked via standard integration interfaces that connect to web applications, mobile devices and cloud services. The network of connected devices, resources systems, partners and suppliers will result in the transformation of
conventional value chains and the emergence of new business models.

Several industries have used the term Model-Based Enterprise for the initiative of creating a continuous digital thread from design 3D models and specifications (a.k.a. Model-Based Engineering) flowing downstream into the supply chain, manufacturing, inspection and aftermarket services of the product.

As stated earlier, Smart Manufacturing includes smart products and smart manufacturing processes. The digital thread must be interpreted by smart product and smart manufacturing processes in order to build to the right product specifications and configuration. Therefore, we see the digital thread as a requirement for smart manufacturing. We also agree that these two initiatives could be worked side by side if the intersection areas and integration is coordinated among the two initiatives and well defined.

QUESTION: Are IIoT and Smart Manufacturing hype or substance?

SURVEY SAYS: Hype with opportunity behind it. The participants believe there is a bit of hype in the media right now but they also believe there is opportunity for big improvements in manufacturing based on the adoption of new technologies and standards into new manufacturing business models. The intent of these initiatives resonate with the audience.

Did I clarify things? Are we smarter now? (Trick question)

Thanks to everyone that participated in the workshop, especially to those who “volunteered” to participate : )

Are Your Manufacturing Operations Ready for Transparency?

What does transparency mean in the context of manufacturing operations? Literally it means we can see through the manufacturing organization into its internal workings. Practically it means full availability and access to information required for collaboration and collective management decision making. It means full disclosure of detailed historical records for root-cause investigation purposes to uncover areas for continuous improvement. It means being open to share our best practices along with our past mistakes so they serve as learning experiences.

Transparency is an essential condition for a free and open exchange and evaluation of priorities for process improvements. It is essential to creating a culture of trust and teamwork in the organization.

Transparency through metrics

The deployment of a performance measurement system with standardized manufacturing metrics is a key ingredient to providing unbiased visibility and transparency within the organization.

In addition to providing a mechanism for transparency, carefully selected metrics can help an organization achieve its strategic goals. Work groups can become more motivated and engaged when their performance is measured according to well selected numeric metrics. Personnel must understand the relation of their metrics to the corporate goals and feel that the targets are achievable. Work group level metrics are considered a better practice than individual employee goals to promote teamwork in the organization. Wouldn’t it be great if all employees understood the corporate goals and how they could make a difference?

Personnel must trust the accuracy of the data and the calculation of the metrics. Manually calculated metrics in spreadsheets can lead to introduction of bias, manipulation of the data and general distrust of the reported numbers. Having a manufacturing system that automatically collects data and rolls it up into metrics avoids these types of concerns and greatly improves accuracy.

Metrics selection

The selection of good metrics and the involvement of key stakeholders can greatly help with the trust and adoption of the standardized measurement system.

Generally we should be able to relate the metric to (a) strategic corporate goals, and (b) to desired outcomes for the customer. If the relation between the metric and a corporate goal or key performance indicator (KPI) is indirect, we should explain and publish this relation so it is very clear to all stakeholders.

It should be fairly straightforward to understand how the metric is derived. This will make it easier for everyone to visualize, trust and relate to the metric.

The consequences of bad performance of the metric should be easy to see on the shop floor. For example, for longer than planned cycle times we should start seeing work orders and planned inventory queuing up somewhere in the work cell. For an increase in cost of poor quality, we should see an increase of rework orders at the shop floor.

The metric should be actionable. It should be easy to derive the types of actions that could be taken to improve performance in relation to the metric. For example, a metric should not combine too many measures into one number because the possible corrective action becomes very unclear.

Metrics should be consistent and independent of subjective bias. A good metric is consistent in what it measures. The source of data, the equations used, and the weighting criteria applied should be consistent but might also evolve over time. When it does change, it should be communicated to all stakeholders. It is good practice to avoid measures where a subjective evaluation is introduced in the calculation. Different people might apply the subjective criteria differently leading to inconsistent results for that metric in the organization.

Accountability and fairness

The organization can set goals to achieve specific target levels on key metrics within a certain timeframe to promote motivation, create urgency, and establish commitments for the team. Accountability in the organization is driven by how performance to the goals is tied to a performance reward system and the actions taken by the management team about poor performance.

For accountability to work, personnel must understand and trust the metrics, perceive the targets to be achievable, and feel that they are empowered to improve performance on the metrics selected for goals. For example, manufacturing throughput rates are constrained by the number of purchase orders brought in from Sales. Increasing the number of purchase orders is out of the control of Operations so it would be better to set performance goals for Operations on something they have more control on like improving cycle times.

In order to successfully set goals and reward systems based on metrics, they must be fair across the organization. But some types of work are harder and more prone to error than others. To be fair with metrics used to compare and benchmark across the organization, it is important to have a method to weigh the difference in difficulty for achieving similar results across the different types of work centers. An example of a weighted metric is the Six Sigma metric, Defects Per Million Opportunities (DPMO). Since DPMO weighs defects by the number of opportunities for defects in each manufacturing operation, we can use the metric to compare performance across different work centers.

Constructive scrutiny

Are you ready for peers looking over your shoulder? Questioning your numbers? Are you used to constructive feedback? The executive management team must be open to bad news and reward the messenger of bad news. Instead of punishing the manager that comes forward, the organization should provide additional budget to that department to help fix the problems. Other managers will get the idea and embrace honest reporting as part of the organization’s continuous improvement processes.

I heard Allan Mulally a few years ago (CEO at Ford at the time) talking about establishing a culture of teamwork and rewarding bad news in management meetings.  Alan celebrated finding improvement opportunities. When he started at Ford, he would ask “How can all the lights in the dashboards be all green when we just announced big losses?” He applauded the manager that brought that first issue up in a meeting. Instead of frustration, he showed enthusiasm and asked, "How can we help you solve that problem?" The following week, he was presented with a rainbow of colors in the charts.

The anxiety can be high in management meetings when there is so much visibility and transparency. It is important to keep the meetings positive with a spirit to collectively address problems and improve the overall organization.

Team buy in

Often it is easier to select a set of metrics than to get employees to buy into the performance measurement system. We listed some important considerations above to improve stakeholder acceptance and trust. Personnel that is not used to being evaluated based on metrics will offer a natural resistance to this new process. The executive management team must express a compelling case for how this new system is linked to the organization achieving its strategic goals.

A few key departments can be selected to pilot the new system. Change champions should be enlisted in these departments and early success in those departments with the new system should have a high visibility celebration.

Evolution over time

Just as a company’s goals and objectives evolve over time so should the set of performance metrics be revisited periodically and changed over time.

For example, for the last two years the strategic goals might have been to reduce cost by 10% and metrics were selected to reduce cost of poor quality and improve labor efficiency. This year the corporation might have a growth strategy and it wants to focus on reducing cycle time and time to introduce engineering changes into production.

Deploying a standard performance measurement system is no simple task but it is a tool to help your organization move up to a new level of business process maturity. It can become a differentiator for your business, and lead to major improvements to the bottom line.