Commentary Feedback on “Third Time Lucky for MOM/ MES!!!! YES, it does have a significant chance this time!!

It is an interesting writing this blog as there is little comment feedback in the blog, but I receive a lot of email on certain subjects with substantial input. The topic of “Third time lucky for MES” I received a lot of both email and discussion face to face, this blog expands on the topic.

The first comment from many people was “that MES has been around for years and has been implemented successfully”, and I agree, but the first 2 generation architectures involved significant services while they have run extremely well for a number of years, but with limited ability to absorb change without significant cost and risk. Also, companies are expanding in multi sites and the requirement to enforce operational practices over multiple sites, again this requires alignment of sites. So yes MES has been successful in concept, but not in a sustaining mechanism.

Charlie’s comment in “The MOM Chronicles” reflects this:

“The first two MOM attempts occurred in the 1990s, and 2000s, actually were also found a primary hindrance to continuous improvement efforts because the MOM system owners were typically understaffed, under skilled, and un governed to support real innovation. “

So what is different this time? Was a common question, as mentioned in the original blog the SOA (service Orientated Architecture) actually been adopted correctly with conforming service contracts at the ERP side and business side with the “Enterprise Service Buses” (ESB) becoming a norm, not just a term. This flowing down into the operational world with vendors looking at aligning with web services, but also model centric alignment vs point integration is key. The figure below taken from “The MOM Chronicles” illustrates the concept:

The experience we have MES implementations at Invensys has pushed us to evolve our architecture, and the key areas are:

1/ The MES functional Capability has evolved in richness

2/ The plant events are now linked into the System Platform, using templates so now plant equipment and events can be templates and managed, also validation is achieved as close to source as possible.

3/ The Human interaction and the business rules and processes are no long programmed they are implemented in a model driven (workflow) environment. So now face plates/ forms that present information and interact with humans validate the data entry as early as possible and with no code but in graphical modeling environments. This area alone is transformational as I have sat down with process/ operational teams with these graphical workflows and worked through with them relative to their process, we mark up the diagram and implement fast. No longer programmers are involved in business rules it is the operational/ business / process teams work know their rules and behaviors they require and they implement.

The diagram below shows the realization of the aspects of the Invensys MES architecture, and it is all three aspects that make this a sustainable solution, that scale, and also work in a multiple site situation. But most of all it is agile aware been able to absorb change.  Again this is a different approach to tradition MES solutions which have at MES Functionality, but honestly depended on coding around the system for events, human interaction and business rules. This architecture is SOA so it is plug and play and services like the MES can run in different locations, leaving open the opportunity for MES data bases and rules to run in an elastic “cloud”, combining with the on premise interactions with the plants and people.

 

Fast Data, data in Context is as Critical as Big Data

I was listening to M2M (Machine to Machine conference sessions), and this interview of Chris Baker from Oracle was fascinating as it echoed what we seeing in the industrial / operational world.

Design the systems assuming massive amounts of data, for not just today but also the future. This means the architecture must be able to access the different data, put it in context, and provide patterns and exception based analysis so decisions and then associated action can be taken.

Data without the ability to take action is of no value, and it is key we move to “intelligent work” concept where information is delivered in context of role, and situation, and associated actions with it. Independent of location, device and architecture, as these will change.

Interview with Chris Baker, SVP, Oracle at M2M WORLD CONGRESS 2013 - YouTube

http://www.youtube.com/watch?v=oqzam6aWqHk&feature=player_embedded

Disruptive opportunity with transitional actives (FAT, training, simulation) for industrial space

As the weeks go on the discussion continues to increase around the opportunities, and growing consideration of Cloud playing in the industrial automation and operations architectures within end users. One of the emerging realization of opportunities in the transitional activities on bringing a plant on line, such as commissioning and operational learning. Not been mission critical activities, as one person put it “why would you want buy and set up hardware for activities such as FAT (factory acceptance testing) or training simulation for only 2 to 3 months?”

The concept of a virtual FAT environment is not new, what is intriguing is the fact that the “cloud” offers expandable (elastic) computing engaged for a temporary period on a monthly plan. Too often the limitation on FAT efficiency is availability of hardware, due to project budgets of purchasing hardware , no flexibility to expand and then the hardware goes to site, restricting the offsite testing and the ability to have multiple FATs happening at the same time. The cloud can easily host the virtual images of servers, control simulators and different workstations of a plant.

Key is that an engineering house can provision the required computing capability in days and test out the loading required computing power required by the application via a cloud virtual environment. They can create a temporary FAT or development environment in the cloud, which can exist for the life of project build, costing is leasing, the system can expand as the project grows or goes through different stages. This is different to a virtual environment in that the computing power in unlimited, and it grows and shrinks with the requirement and it avoids out of date hardware with no home.

Another end user discussion is relative to training simulation. Traditional OTS (Operating Training Systems) programs expect a long term steady state of training capability, but as the initial project go live, and the evolution of existing staff, and associated staff they have a temporary requirement for significant operational and worker training systems, and again " cloud seems ideal for this". The fact that a simulation OTS can be set up and then expanded, accessed from different locations, and then dismantled after the demand drops without the need to by unnecessary hardware is key.

Both of these examples are not earth shattering, but the discussion and questions show a shift in thinking. I am fully of the belief that a typical automation/ operations architecture which spans geographical boundaries and even within a plant, will be a HYBRID architecture in the next 3 to 5 years. With on premise set of applications, (probably upgraded versions of the existing ones on the site today), and with a set “cloud” based applications either on private or pub that work in a complementary fashion with the plants. Providing additional richness to the site applications with extra computing power to execute applications such as simulation (“What if”), for training, knowledge systems, and cross plant applications such as history, information, and decision support. The development of security architectures that accommodate the cloud for industrial space, where security access is handled external to plants fire walls, combined with the plant firewalls, providing significant security.

Another example comes from a recent paper from Analysts ARC on MOM/MES customer interviews which stated:

“Another implementation timesaver to look for is the availability of cloud-based MOM/MES system for development. Compared to waiting for on – site servers and data bases to be acquired, deployed, and configured; the cloud-based  system can be often be provisioned in a few hours so the team can get right to work. If templates are also used stake holders can immediately begin to make system decisions that otherwise might take weeks or months to reach and base these on the best possible information, the actual system behavior.”

As we have seen over the last 6 to 8 months the discussion grows around using the cloud, especially as the cloud based industrial applications continue to be released to market, and the next 6 months will see a step increase in these. The time has come to understand what the requirement is for the  business ,then ask the question which is the best way to implement this in a scalable and affordable low risk manner.

Operation Intelligence(Enterprise Manufacturing Intelligence) vs Business Intelligence (BI) the Difference and it are the time it be recognized!

So many times when I visit a customer site or discuss with product develops, or engineering houses people get confused over what are the roles of each system, and they must work in conjunction but they not the same. Especially when companies already have a business Intelligence strategy and tools, but they also have process analysis tools (trending) but let's move the focus away from engineers to the consumers of the information and their transforming role in achieving operational excellence.

The question of “why a company should implement an EMI solution if they already spent money on a BI solution. They already have the “slice and dice” and analytical ability within BI, so why waste money on an EMI solution?”

The realization is that users in the real time operations require empowerment capability to make decisions, to be able to access “trust worthy information” quickly and easily. Quickly seeing status of plant, operations, and easily been able to apply limited operational analysis to answer well known “Operational situational questions”. EMI and BI have different purposes, and they are aimed at a different audience. Manufacturing-specific reporting and intelligence are different in content, context and data frequency than the data in BI.

I had a long discussion with Gerhard Greeff (Divisional Manager: Bytes PMC, MESA trainer), on this subject, and he totally agreed in the miss understanding, that people have and how often they tried to use BI tools to build operational dashboards for operations and they do not get accepted or used. Also, this exercise results in significant IT projects to build the tools, and gather the data, so often to be far less effective that MS Excel, which many operational people will configure what they want. The requirement now is for consistency of information, and measures, causing a transformation in the market caused by “Apple” that time to access and value is far more critical than “perfection on information layout” introducing the concept of “good enough” will do. Like we do on many applications on smart phones where down loaded applications based upon a functional need, and have limited ability to change it, except the basic configuration, but it works and is delivering value fast.

You may be asking can you clarify the difference, so I have used some text from Gerhard’s paper in “The Mom Chronicles”.

“Data in a BI solution is typically at the same low frequency as that of the ERP system such as daily values. For a Plant manager that wants to know what is happening on a shift or hourly basis, BI will thus be inadequate. BI tools are typically not designed and implemented to take into account the real-time nature of manufacturing operations and its very large data rate. As such, BI are not able to handle the high frequency of data receipt and the required fast response-times of reporting/visualisation required by manufacturing operations.

Executives use BI as strategic analysis and decision-making tools for the company. From their BI systems, they can see the profitability of individual plants and sites and, as such, can make the decision to close down a plant or to change the manufacturing strategy. They typically work on confirmed and validated numbers and results as they want to ensure they have accurate data when they make the decision. These validation/confirmation or auditing steps often add considerable time between the actual event and the time the data end up in the BI solution.

Site-level production personnel however cannot wait for the niceties of auditing and validation before they take action. If a report or an EMI dashboard indicates that something is wrong, it is their responsibility to investigate and take corrective action. If a feed-rate is lower than planned, the production manager is not going to wait for the confirmed result in the BI system tomorrow before he takes corrective steps. No, he is going to investigate or have someone investigate for him. If it turns out to be a false alarm, then he is glad as it is a crises averted. If something is wrong, he takes corrective action, or at least knows and expects the bad results from the BI system tomorrow. Production executives hate surprises, even good ones.

EMI systems thus have a two-fold purpose:

1. To provide early warning in real-time for potential problems in order to make decisions or take action, and

2. To provide “slice and dice” data on historical data and Operational data for process improvement, and operational status, delivering the information in time, equipment, and operational context.

EMI has data available at the granularity and frequency delivered by the individual applications. This can be from seconds to days, depending on the specific operations requirement. The data is also available per individual piece of equipment, line or processing unit and can also be rolled up into hours, shifts, days or weeks for any of these. The granularity of EMI systems is closer to real-time, and they are often used as real-time dashboards for Operations Executives.

BI may be able to provide the historical “slice and dice” data, but typically, not at the level of granularity required by operations managers. BI will not be able to provide the real-time early warning required by the plant. Both of these are thus needed to support manufacturing companies adequately.”

The challenges vendors have is how to deliver this operational information in a rapidly consumable form, with minor time and effort outside of operations. The system will need to evolve, with more operational questions answered out of the box, or an experience which enables operational people to answer these questions.

Role of IT changing from Central IT to Consultant IT as new devices/ and services become absorbed into the industrial architecture?

I thought this paper (below) introduced a fascinating discussion on the changing role of IT, from central IT to more of a guideline, consultant to management of devices and services in an organization. In the industrial space,  we have seen leading companies go from enforcing mobile device (the one issued by the company) to issuing one, but also allowing employees to bring in their private preference of the device and connect it to the corporate network and use it in the day a to day work job.

 This research is necessary, because it reflects and profiles a new order in directing and controlling the use of information technology, which we need to expand » 

Business Leaders Spending On Technology Because It's Too Important To Let I.T. Go It Alone

www.forbes.com

By John McCarthy In the Forrester report, "Tracking the Renegade Technology Buyer", we uncover the motivations and technology spending priorities of over 1,000 John McCarthy North American and European business executives. The data from the Forrsights Business Decision Maker Survey was collected in Q4, 2012. Of the 891 respondents that had a budget [...]

This trend will only continue as the Gen Y and Gen X will not put up with different experiences, therefore different operational processes. Another trend is the rapid mind switch from having to build specific applications for me or my plant/ role, to accepting “good enough” applications that can be down loaded and up and running in minutes, with limited configuration. Providing a significant increase in information available and for that last 20 to 30% that comes with custom systems people are questioning the time, cost and sustainability. This mind shift has come with home, commercial experience of the applications on the “Application stores” just search and select one and accept the value it brings the expectation is not that I can customize it significantly.

Example the applications below provide in a 10 minute setup and download (as long as the site has the remote connector that publishes the data to the cloud in a secure manner) 80% of the information many roaming workers need. Is it ideal layout reports in standard corporate format no, but it is “good enough” and is self serviced by the user delivering significantly more information than they have today.

On the back end systems,  the same is happening as the acceptance of SAAS and managed services within the Industrial Operational architecture grows, the need to have IT infrastructure reduces ut the capability grows in computing and capability by leveraging the service provider. IT will have to manage these service providers and plug them into the industrial architecture in a secure way that is aligned with the IT guidelines of cooperation.

One discussion this week was with large process company, and they said why would they use “cloud” in their operations they have covered in their industrial automation/ operations systems. This contradicted the operations team in the same company who are concerned about operational continuity and uptime, and with the increasing upgrades, security patches, they looking for the maintaining vital decision support capability at higher availability, a key advantage of a managed service is the increased availability. Combine this with the need to increase the information on an issue to a worker so decisions can be made faster. The discussion shifted to the requirement for understanding the “future” through “what ifs” and how that can be made available to all workers. This is near real-time activity, and could e a service hosted in the cloud (public or private) consumed by the users as needed,not all the time, but the computing power will need to elastic. It was not long before the IT member of the discussion was seeing the opportunity, and asking more questions, this will be increasing situation/ discussion over the next 12 months in the industrial sector.  

The growing influence of operations, and how to empower operational decisions in an increasing climate of workforce transition, and rotation, the acceptance by IT of using my device, and allowing these applications. Shifting IT’s role from not providing as this is coming from out side either with the device or from the service provider, but to consultant that provides guidelines and maintains the integrity of the security system.

Interesting thought and trend!  

Information vs Data Leads Discussion on the Future of Operations!

“Gather all the plant data and analyze afterwards” are common words you hear about the market, but when the discussion happens this approach a “putting head in the sand” approach, with limited bigger picture consideration. Today the key to agility is empowerment of decisions and actions in the NOW. This does not require data it requires trustworthy, in context information.  The last couple of weeks has enabled some fascinating and productive engagements. In a discussion,  last week at a Mining Thought leadership on the future a sizable group of interested people attended and took part in discussions.  

A key concept of “mine of the future” and actually for most industries oil and gas, power, food etc. is the agility to take more holistic operational view of the system and day to day operations. This requires alignment at 3 loops (the diagram illustrates these loops) of operations with the alignment in decision and actions. Foundational to this is the information that decisions are based on, requires not HISTORIANS but Plant/ Operational Information Systems, that align information and actions for effective use my different operational roles. Companies that make this foundational move will have a system where data structure, validation is “managed” not coded, that the system is trust worthy so people will depend on and use the system.

To many times the discussion with mining and process end users who are implementing an information system for increased decisions support, that they require a re look at the data sources and how to put it in context, and validated. An example of this was a coal company in South Africa they had spent significant time working on an information system and the historians and data warehouses, but lost effectiveness through:

• Data alignment across sources, E.g.| Finding different data streams that effected the same asset calculation for say energy.
• Data validation
• Data structure

The conversation remarkably quickly ended up going back to redo of the structure of data coming into the historians, and getting this data structured, validated before it went into historian. They had two choices either going to source in this case PLCs and adjusting the running code (not a smart idea), or put a structuring layer in which would structure the data, validate the data, and provide high availability and single names space to manage over the distributed historians.

This is a departure from the story he was told that just put a historian in and capture the data worry about analysis afterwards, that is old and in effective saying. As discussed in the “mine of the future” discussions  the challenge is to “federate” the existing data sources on a plant, E.g.| Historians, alarm event data logs, operator logs, and delay, downtime data bases, E.g.| The alignment of the data sources into effective information that actions can be taken. The concept of “self service” becomes necessary, as there was a lot of comment around of trying to minimize the process analysis phase and role in the data, and try to get effective information to operational people quickly. Another example is an oil and gas plant’s decision system that is effectively been run 24 hours out of phase with the plant, by only have decision able reports/ dashboards from the past 24 hours at 2 to 3 in the afternoon so. Again this delay was due to data gathering, data alignment, validation, in MS Excel manually done by 3 people, the company was exploring ways to eliminate this manual creation, so the whole process is “near real time”.

A clear message from the last couple of weeks is we need to step back, align the existing systems, to provide that key foundation for operational empowerment, absorb significant milestones such as advancement in the communication infrastructures; Example putting 4G communications in the Pilbra mining area (remote north western Australia), providing significant data capability. (A topic for next week). This need to absorbed into the industrial / operational Architecture, internet will be a natural part of the backbone, leveraging computing power remotely for functions, such as storage, analysis, model running, help accelerate the decision support.   

Third Time Lucky for MOM/ MES Architectures?

For the last 15 to 20 years companies have implemented MES (Manufacturing Execution System)  systems, and MOM (Manufacturing Operations Management) systems, remembering MOM is a super set of MES. These implementations executions have been both custom, and using off the shelf applications for MES, and success has varied, but even the successful ones are struggling to evolve to current agile requirements due to the method of implementation. One end user asked me on the flight “has MES been successful?”, I stepped back and thought about a couple customs who have implemented end to end MES. Based on one MES system so that manufacturing master data is managed by one system, with the customer stating their MES has been the most valuable software implementation on the plants, it just works and is the heart of their manufacturing. So the answer is yes, but the fact of the question allowed me to reflect on the normal bumpy roads MES implementations have had.

I was read Charlie Gifford’s latest book “The MES Chronicles” (ISA 95 best practices book 3.0), which has a set of articles around Gartners’ Manufacturing 2.0, explaining the concepts, and reality to the concepts. It is well worth the read if you are looking at the industrial/ manufacturing operations space.

 

 

In the introduction,  Charlie does an excellent job raising the challenges of MES, and the fact that we now with Manufacturing 2.0 going through actually the third architectural attempt at MES. How true his comments are when I reflect on my own career which had gone through all 3 since 1995 when we released InTrack (original MES Product).  A key consideration to this discussion is that MES is a concept of managing the executing the manufacturing, with the off the shelf solutions and customer systems built for a particular industry  with rules and practices for that industry. So looking at Invensys’s first generation MES system InTrack it was built for the semi conductor/ electronic industry, and the outstanding success stories I referred to were from that industry. Invensys’s second generation product built Wonderware MES for food and Beverage industry, and again has worked remarkably well in that industry and related industries. This does not mean they cannot be applied in other industries, but the “glove fits well”. That is why I do not like the generalization of MES, we should categorizing them by industry types, to help selection, and stop companies force fitting the wrong models into their practices.

Charlie in his book reflected on the three generations of MES/ MOM as:

“20% of advanced manufacturers discovered that the first two MOM attempts lead to:

• High cost MOM systems with extremely poor data integrity
• High cost change during new production introductions, production scaling time to market and continuous improvement.”

“ The first two MOM attempts occurred in the 1990s, and 2000s, actually were also found a primary hinderance to continuous improvement efforts because the MOM system owners were typically understaffed, under skilled, and un governed to support real innovation. “

His % might be low, but the point is that MES / MOM solutions have typically been architected in a “point to point” / application integration, with high levels of customization restricting evolution to the original developer. Many of the original InTrack MES implementations have maintained the database well, and the rules within it, but significant custom code has been developed for human interaction and data validation, and data validation on automated events acting on the system.  Like highly customized ERP implementations the ability to evolve , upgrade the systems become an anchor on manufacturing agility. Yet that is the reason why people put these systems to increase efficiency and consistency of production, but the issue is manufacturing practices, new product introduction is constantly changing and evolving, and the systems must be able to absorb this change naturally if the implementation are going to allow for the required agility needed today.

So the third attempt at MOM with the Manufacturing 2.0 concepts undoubtedly lead to:

·         An SOA (service orientated Architecture) that allows plug and play of the 15 to 20 Operational applications required to run a plant, allow the inter-operability to set up using messages through sustained services vs application integration.

·         This integration is a model based using tools such as workflow and sustainable environment.

·         Validation and data entry rules will be model driven, so that embedded best practices, that can evolve in a sustainable way as staff evolve in the organization.

·         Semantic information, and data management models based on proven models such as ISA 95 will enable existing and different models of the different operational applications to align.

The book outlines many of the concepts. MES are not a standalone product, it is  an architecture that merges level 2 events from automation, with validation of data, events in a structure asset/ operations model that can interact with the different operational applications through the life of a manufacturing operation. Key is the acceptance of  architecture which has model driven interoperability (so the model can evolve with governance) and the introduction of workflow to be a natural part of the operational system to capture the procedures as embedded operations that again have governance so can evolve as the practices of the plants change. Like successful ERP implementation, customization must be avoided, configuration within the tools provided make the system sustainable, but this will be a mind shift for people. Too often people talk about APIs, and taking coding tools to build a solution, this is fine for the short term, but will come back and bite when time for change and evolution. The project and program owners at the end users need to take a more holistic view and enforce an architectural cadence of configuration vs programing and making sure the “human to application”, and “application  to application” integration are model centric approach where configured services  using workflow configuration is key.