ISA-95 is a missing link in Smart Manufacturing. Let’s talk about why ISA-95 should be in mind as you’re planning your roadmap for executing various Smart Manufacturing concepts in your plants.


Smart Manufacturing creates a lot of new value for manufacturing by providing new technical tools to make manufacturing products more efficient and flexible. These tools also provide new sources of valuable data to understand the current status of operations, identify issues that were previously unknown, and provide information for how to take corrective actions. However, the success of companies will depend not wholly on concepts like Smart Manufacturing by providing better tools and processes, but rather more on valuable data for having a better understanding of operations and making better decisions. This requires sharing valuable information in real-time to everyone from operators on up through the organization.

The ISA-95 standard provides ideas for how to exchange data and share information using industry best practices from ISA. This standard simplifies the decisions for how to structure the data and share it across the organization. This simplification then can pay dividends in the long term.

Smart Manufacturing

The ideas behind Smart Manufacturing and Industrie 4.0 have a lot of merit and value, such as combining various new and old technologies in various ways to attain more efficient and flexible operations. If a company can put these concepts into practice, they are well on their way to creating a competitive advantage by producing more with what they have, reducing costs, becoming a more flexible company, and succeeding in the market. However, the more efficient and flexible tools and processes will only take the company so far. The data from those tools and processes is where the real value is. Data is the real gold to mine in any manufacturing company. However, that raw gold out of the ground isn’t as valuable as when it’s in the form of ingots. Therefore, the gold as well as the data much be processed by adding the operational context, so it provides optimal value to the end user.

Issues with Data

However, companies have a hard time mining for that gold let alone processing it into very valuable ingots of information.

Companies are often riddled with several issues regarding their data:

  • There is a lot of valuable data held captive in paper and spreadsheets. The data is often valuable production, process, and/or maintenance data which, when made visible from the plant floor to the top floor can provide clear, indisputable insights on issues to solve.
  • For the paper and spreadsheets that have been eliminated by digitizing the data in IT and OT systems, much of it isn’t visible to the people that can use it.
  • Even if the data is digitized and visible, often that data shared between systems is done in Point-to-Point solutions, which are very problematic. One integration of production data to an ERP system might be via automated spreadsheet file transfer and import. Another between a CMM and a LIMS via an API. These direct or point-to-point solutions will multiply, be implemented with little to no longer term planning, and frequently are undocumented. This becomes an IT nightmare. One change in part of the system might bring down part of this IT house of cards and cause very expensive downtime in the plant.
  • When data is shared it is often without appropriate context (e.g., where the data came from, what the data means, how the data relates to various processes, etc.). This data then often lacks the significant value required to be useful.

Two Solutions

There are two concepts to be applied to this situation in tandem to enable a company to provide information with the highest possible value to its team members to drive greater efficiencies, production, and growth.

Data Driven

The first concept is Data Driven decision making. Data Driven companies have a single version of the truth (accurate and timely data that isn’t duplicated across the company), shared with everyone in the organization (to the extent data permissions allow) in a tool everyone can access and know how to use, and everyone knows how to identify problems, make decisions and most importantly take action on that data.

Having access to this “single version of the truth” is crucial to the future success of companies. This means eliminating silos of data, getting rid of most spreadsheets used for recording data and running business processes, digitizing paper-based systems, and pulling valuable information from existing and new sources in the business. These new sources of data could be from new Smart Manufacturing tools and processes, including IIoT. Companies of all kinds, including manufacturers, should be using more of the critical data in their organizations to create a competitive advantage with the data.

To make this idea of Data Driven decision making work, there is hard work to be done at any company where the data needs to be acquired, exchanged or communicated over a network, cleansed, and contextualized. This process of acquiring, exchanging, and contextualizing can be done, in part, by using ISA-95.


Let’s do a very quick review of what ISA-95 is. First, ISA is the International Society of Automation. They are a nonprofit industrial organization that puts out the good word on how to improve manufacturing companies with standards and best practices around machines and automation of those machines. ISA-95 is a standard defined by the ISA which provides a single definition of terminology, operational models, and information models about those operations, along with ideas around how that data should be exchanged. These definitions become the foundations for how manufacturers can organize and exchange data within their organizations in a way such that the data provides the highest value possible.

A key to making Data Driven decision making a reality is to add context to the data. By context I mean that the data is identified with specific processes in manufacturing and can then be combined with other data to allow for more wholistic understanding of and decision-making around that process.

For example, let’s say IIoT (Industrial Internet of Things) is used to pull new process data from a batch system for making soups and broths. Maybe the data is from new sensors and a new data capture system for measuring quality, including temperature, pressure, volume, and salinity. The data is captured for each batch and then analyzed to look for leading indicators of lower quality product to then find causes of lower quality. A list of temperatures, pressures, volume, and salinity over time by itself is of modest value when viewed by an operator. That operator needs to have a full understanding in their head of the manufacturing process, what the limits are for these values to produce a high-quality product, etc. Due to various challenges including an aging and retiring workforce and challenges around hiring new people, it could be less likely someone will be operating the equipment with that full level of knowledge.

Therefore, the data around that operation is more valuable to the organization when it is put into the context of production control, recipes, quality standards, etc. Data from other systems can be more easily viewed alongside the process data to understand the various processes and events that occurred when producing certain batches and how quality of the product might have been affected. This data can be viewed relative to various parameters that indicate high- and low-quality product.

It is then easier for the operator to understand the current operations around that product, make decisions, and most importantly take action to maintain the quality of the product and/or to handle adverse events as they happen, not after the fact.

In this soups and broths example, ISA-95 plays a big role in:

  • Providing definitions of the operations of the manufacture of the soups and broth,
  • Defining events in that process where sets of data should be sent to other systems,
  • Providing a structure to that data such that it is more valuable with a context of the specific operations, and
  • Defining a basic architecture of how the data should be exchanged (i.e., publish/subscribe architecture).

This kind of solution then has the significant benefits of being:

  • Scalable for more machines, lines, and plants
  • Flexible to add new capabilities without
  • Systems are abstracted from one another so that one can be changed without breaking the sharing of information from other systems
  • Agnostic to technology from various vendor systems that integrate with this solution
  • Reliable over the long term
  • Lower cost over the long term

Those benefits are appreciated. Ultimately, however, the point is these kinds of solutions based on Data Driven decision-making and implemented with ISA-95 standards in mind will help manufacturers accomplish the goals of Smart Manufacturing, which are to run a more efficient, flexible, and competitive organization in their market.