How Can My Department Use Manufacturing I-IoT Data?

Introduction

There is a growing recognition of the value of the data from Smart Factory systems such as I-IoT (Industrial Internet of Things). The focus for most of these projects is highly focused on improving machine performance and manufacturing quality. However, there are many additional uses for this data across all departments of an operation.

These other uses are the focus for today.

Typical Use Cases by Department

The list that is presented here is meant to be more illustrative than comprehensive. There are many more use cases for this data within each department that are not covered here. But this list should be a good way to start thinking outside the box for how data from the shop floor can be used across departments.

Operators

The data from these systems can be used to augment operator capabilities in many ways. Let’s look at a few of them:

Digital Visual Controls

One benefit that can be provided to operators is real-time feedback on the process performance. This can be achieved through digitizing visual controls on the shop floor using information coming directly from the machines, sensors, or other equipment. This feedback allows the operator to adjust the process to improve performance or quality and helps them meet their targets.

Digital Work Instructions

Digitizing work instructions enables less experienced operators to support single piece flow and unique builds in sequence. In addition to the instructions for the operation itself, these systems can reduce non-value-add paperwork by automatically capturing process inputs. They can also provide real-time feedback to deviations from the standards.

Performance Monitoring & Optimization

In addition to providing basic performance monitoring solutions, these can be augmented in such a way as to help the operator perform better, as well. For example, at one customer we used the detailed information across shifts to show each operator where their performance was strong relative to their peers and which areas they could improve.

Setup / Changeover Support

This topic is the subject of a previous webinar & article, so I won’t go too much in depth here. In brief, the data from the I-IoT systems can be used to break down the process into its constituent steps and provide timing distributions for each. After the SMED event, the systems can be used to monitor the setups and ensure they are being performed as designed.

Maintenance

Some of the traditional use cases for I-IoT systems appear in this department. For example, many of these smart factory solutions are targeted at predictive maintenance capabilities. In this section, we’ll highlight some additional areas of opportunity.

Automate Ticket Creation

By providing integration between the smart factory system and the customer maintenance management system, it is possible to automate the creation of work orders when machine downtime occurs. This has many advantages of speed, ability to supply failure context with fault codes, performance data and more.

Optimizing Preventive Maintenance

Few companies have a regular process of evaluating their PM tasks for their impact and whether they should continue to be performed at the same frequency. Detailed performance data from the machines allow for thorough analysis of these tasks so that every required PM is performed…but no unnecessary PM creates waste.

Condition-Based Maintenance

It can be expensive to set up, train and maintain predictive maintenance models for complex machinery. On the other hand, it can be very simple to set up I-IoT systems to monitor hundreds of process variables and identify when they vary outside of norms. Implementing condition-based systems is a highly under-used benefit of smart factory systems.

Smart Tools / Tooling Optimization

Along with Sandalwood, we at VDI have worked with customers to optimize tooling usage based on the detailed information coming from the I-IoT systems. As with machine maintenance, this can be accomplished through sophisticated predictive models and through simpler condition-based models in some cases.

Facilities

The broader Facilities team can also make use of the smart factory systems and data. I’ll be cheating a bit in this section, as I will be looking at how those same systems can monitor non-production equipment in the factory to get value.

Energy & Utility Consumption Monitoring & Optimization

This can be a quick area of payback for any I-IoT implementation. By putting some cheap sensors at each machine to monitor energy consumption, it is possible to identify waste when the process is not operating. This is on top of the benefits of having that information for predictive capabilities at the machine itself.

HVAC Monitoring

All the techniques being used in I-IoT systems to monitor and optimize production equipment can be applied to HVAC and other facilities equipment. This can be another area of quick payback that is essentially free along with the production uses of the technologies.

Cold-Chain Certification

For industries where cold-chain certifications are required, I-IoT sensors and systems can be used to always track the locations and environmental conditions of materials. The systems can then be configured to produce certification for all materials that require it.

Fork Truck Optimization

In large facilities, fork truck (or other material-movers) availability can itself be a production constraint at times. Using simple integrations between equipment location data and material movement requirements, it is possible to optimize fork truck usage as well as lower-tech equipment such as hand-carts.

Material Management

Along the same lines as the above, the Material Management team can make great use of the data from the I-IoT systems. Because those systems can have visibility to real-time production status and also the upcoming schedule, it is possible to enable several improvements to material management.

Material Consumption Tracking

Whether a manufacturer is utilizing Kanban techniques or more traditional material management methods, digital visibility of materials usage and upcoming requirements can help optimize the flow of materials out to production.

Lot Tracing

Many companies lack visibility of which supplier lots are being used for production at any given time. With some changes to other procedures in combination with information at the point of use, this information can be tracked in much more detail. Additional uses for this information will come in a later section.

Early Changeover Notification

In operations where there is a need for kitting of setup / changeover materials, getting early notification to everyone required is critical to minimizing downtime. IoT systems specialize in not only tracking when that upcoming change will be required, but also being able to notify a flexible list of people based on the unique requirements of the process and from/to combination.

NCM Management

In addition to collecting information about the manufacturing process for good parts, the smart factory systems should be implemented to cover rework and other non-conforming material processes. This allows information to be captured and analyzed much more thoroughly for good and bad parts.

Quality

The Quality department has many different uses for detailed production information. The I-IoT systems can be used to track test results and other quality information directly. But there are many ways the production information can be used by Quality, as well.

All Data is Quality Data

In the end, all data that’s collected from the shop floor is information that can be used to analyze contributing factors to poor quality. Whether that is environmental information or detailed tag data coming from the machines, this information can be correlated to the test information to identify potential causal factors and leading indicators.

SPC Automation

For many companies, statistical process control (SPC) is a manual process that requires manual math from the operators. Other companies have dedicated systems for SPC, but many of these systems are data islands isolated from any other analysis. Smart Factory systems can not only automate the SPC process itself, but also blend that data with other information from the shop floor to drive much deeper levels of analysis.

Documentation / Certificate of Compliance

For many companies, they require a certificate of compliance for orders that are being shipped out to either certain customers or all of their customers. Smart Factory systems have the flexibility to support gathering all the required data from the process itself or through integration with other systems and then output the required documentation in the required formats.

Six Sigma Support

There are many tools in the Lean Six Sigma toolkit that require extensive data for the analysis. I-IoT systems can provide the required data, as well as be configured to augment or automate much of the analysis.

Process Engineering

The Process Engineering team (and Mfg Engineering) also have a lot of different ways they can use the information from these systems. Naturally, they would be involved directly in the machine monitoring and uptime improvement efforts that would be the primary focus for the implementations. But there are some other ideas below for how they can use the data.

FMEA Support

Performing a Process FMEA is a very valuable activity that is not performed very often because of how long and involved it is to perform one. However, much of the data collection that needs to take place during the process can be automated using Smart Factory solutions. In fact, these tools are normally implemented with the express purpose of tracking the various failure modes and effects of those failures. Supporting the pFMEA process is really a simple matter of implementing the solution in the right way and then using the data.

Bottleneck Identification / Line Balancing

Depending on the structure of the manufacturing operation, the data used from the individual operations can be used to identify how to better balance a linear flow process or to identify and relax the true bottleneck(s) within a manufacturing process.

Work Instruction Authoring

In addition to delivering digital work instructions to the operators as outlined previously, these systems can be used to help author and optimize those work instructions in the first place.

Factor Analysis

Factor Analysis is the identification of different factors that contribute to manufacturing performance, whether they be environmental such as temperature or humidity, supplier or material related, machine setting related or anything else. Having these systems in place allows correlations to be performed on this information historically instead of having to run tedious and potentially expensive DOE experiments to determine the level of individual factor contribution.

Environment, Health & Safety

The EH&S team is not usually the first one people think of when implementing I-IoT or other Smart Manufacturing solutions. But those tools and their data can be very useful within these teams, as well.

Monitor for Safe Operating Conditions

In extreme cases, we have worked with customers that manufacture with volatile substances where the operating conditions are absolutely critical to worker safety. But even in normal environments, monitoring machine pressures, temperatures and such for deviations from normal can help to ensure as safe a work environment as possible. And when accidents do happen, having a record in place of what was happening at the time can be crucial to understand the root cause of the issue so that it can be prevented in the future.

Workforce Training

A strong feedback system is crucial to initial workforce training as well as continued improvement over time. The data from these systems can be used to provide that feedback and identify where reinforcement of the initial training may be required.

Track Certifications for Current Operator

By tracking who is at a given station, what certifications are required, and who has which certifications, these systems can verify in real-time whether or not the worker at each station has the training required to perform the given tasks and alert when it is not the case.

Monitor for Standard Work Compliance

There are many systems available now that can not only collect detailed information from the machines, but also utilize video to monitor the manual activities being performed by the workers. These actions can be compared to the standard work and exceptions can be immediately flagged and alerted. This can help prevent safety issues where workers are not following safe working practices.

Operational Excellence

The Operational Excellence team may benefit more greatly from these systems than any other group. Nearly every activity this group performs can be enhanced through the data coming from the shop floor.

Improved Problem Solving & Root Cause Analysis

This is perhaps the most critical area where the data should be used more extensively than it is in most implementations today. With data available from nearly every aspect of the shop floor, every problem solving activity should be centered around analysis of the information from the process and how to drive to the (typically multiple) root cause(s) of the issue. Even something as simple as generating the proper description of the problem in the first place should be centered around the what the data is reporting.

Lean Tool Support

As with Six Sigma above, most lean manufacturing activities are ultimately built on data. Whether it is explicitly building the lean tools into the solutions themselves or simply using the data to perform something like a Value Stream Analysis, the information is available to make all the tools in the lean toolkit more effective.

Event Prioritization

When looking at the potential project funnel for improvement events, attention should be paid to the potential impact of the event. This can best be measured from what the data says. Other factors need to be considered, but a large part of that event prioritization should be based on that potential impact.

Fighting Entropy

In conversations with many lean leaders over the years, they have identified “sustaining the gains” as the single biggest challenge. There is a very real performance entropy that takes place over time as product mix changes, operators move between jobs, machines age, and other changes take place. The new levels of productivity established after running simply don’t last unless additional energy is put into the process. Implementing these solutions to monitor the process afterwards and identify when the entropy takes place can help to eliminate or mitigate this problem.

Planning

The Planning department can also benefit greatly from the shop floor data. Here are a few ways to take advantage of the information to create more accurate, timely and feasible production plans and schedules.

Current Status of Shop Floor

When generating a detailed schedule for the next few shifts or days of production, one of the most important factors is the accuracy of the starting conditions in the plant. Which machines are currently running which parts, what percentage of production lots are complete at the current operation, which resources are currently available and more all come into play when trying to generate an optimal schedule.

Accurate Operation Durations

Generating a plan or schedule without accurate durations for the operation times is like trying to navigate with an inaccurate map. In addition to all the other information being collected by these systems, they have a very precise picture of how long options actually take, as opposed to what is stored in the ERP system for costing purposes.

Accurate Setup Matrices

Planning around setups and changeovers is often an exercise in guesswork. Many companies only have a vague idea of how long changeovers actually take, with very little detail around the factors that drive a two hour setup versus one that takes eight hours to complete. All those details can be filled in through data capture in I-IoT.

Monitor Adherence to Plan & Adjust

Once a plan gets published to the shop floor, it is often immutable until the next day (or longer). The shop floor data can not only show the current status of the plant, but can also compare that to where it should be based on the schedule. If the gap is large enough, this could kick off an update to the plan to better reflect the current reality.

Finance

The operation durations not matching reality is briefly mentioned above in the context of the Planning department. But that information and much more is also critical to Finance.

Improved Overhead Allocations & Standard Costing

More accurate data from the shop floor can be utilized by the Finance group to improve their cost estimates and overhead allocations. By gaining visibility to the actual resource consumption in the process of manufacturing each product / order, the Finance team can be much more granular in their analyses.

Hard Data for Project / Spending Evaluation

The potential payback is often very fuzzy when the Operations team makes requests for funds to purchase new equipment, run improvement events, or other projects. By implementing a process of using detailed data from the shop floor to illustrate the operational impact of suggested projects, Finance can more accurately evaluate whether to approve funding.

Improved Budgeting Inputs

The same analysis applies to the annual budget process. With much more detailed visibility on the value provided by different resources and expenditures, Finance can make better judgements on whether those items should be approved for the next budget, as well.

Plant Manager

In addition to the functional groups, management also benefits from the data coming from the shop floor. Many of the regular reports looked at by Plant Managers can either be automated or greatly enhanced utilizing the data from Smart Factory systems.

Real-Time Cost Variance

Variance reports are one of the staple tools of Plant Managers across manufacturing. With data being collected and processed in near-real-time from the shop floor, it is possible to automate these reports to show profitability status throughout the day.

Virtual Gemba & Visibility

Nothing should ever replace performing Gemba walks out to the shop floor to see things with your own eyes. But being able to get real-time reporting as you make the walk can make it much productive. A digital status board also gives the Plant Manager visibility to what is happening at all times.

Single Source of Truth

One frequent complaint from Plant Managers we’ve worked with over time has been that each team will show up to staff meetings with their own set of data and half the meeting will be an argument over which one is the truth. Collecting comprehensive data from the shop floor through these systems can end those arguments by providing a single source of the truth.

Data Tracking & Reporting Waste Elimination

How many hours does your staff spend doing manual data collection, manipulating information in Excel, and generating reports for you or for corporate reporting? What else could they be doing to instead use automatically generated information to actually improve the problems the data highlights?

Corporate Operations

Our final group is the Corporate Operations team. This is everyone in that structure from the COO on down, so it covers a lot of ground and an awful lot of potential use cases here. If nothing else, having that same basic visibility that we talked about for the Plant Managers would be a huge boon for many corporate leaders.

Best Practices: Benchmark & Share

As these systems are implemented, it is important to configure them to capture work practices. This enables the corporation as a whole to be able to compare the practices across the different plants, identify what works best in different environments, and share those learnings across the company.

Problem Solving Data Sharing

Also, while the detailed process data is being collected at the plant level, it should absolutely be shared across the entire organization. When implementing something like predictive maintenance capabilities, more data is (generally) better data. Wherever there are similarities across the organization, the teams at corporate and in the plants should be able to leverage the information from the whole company when looking at individual problems.

Performance Scorecards

Every organization uses some kind of KPI scorecard for weekly / monthly reporting and management. Operations executives will often have a regular cadence call with the plants to review these KPI and what is being done to fix any “misses”. These reports usually require massive manual efforts to create and keep up to date within each of the plants and to collate at the corporate level. Instead, the information can be “bottled at the source” and automatically aggregated up the chain.

Digital Management Operating System

Toyota is famous for creating the Toyota Production System that outlines how the company manufactures its products and defines most of the support processes that makes things tick. Many other companies have adopted similar production systems to provide structure for the operations team. A Digital Management Operating System takes many of the ideas discussed earlier in this document and brings them together into a single framework that creates a digital version of the operating system.

Summary

As can be seen from the sections above, there are many uses for the production data and systems beyond the traditionally narrow use cases. Whether you are just starting down the path to Smart Factory solutions or whether you have a mature implementation already in place, there are likely many additional ways your company can take advantage of the information you are collecting from the shop floor.?