Starkly stated sustainability targets such as ‘Net-Zero by 2030’ imply an inherent struggle, and while this may be true in certain arenas, there is a genuine opportunity to achieve environmental goals, automate accountability and improve profitability within manufacturing – all at once.

In this article, we’ll outline exactly how the right capabilities, infused with expertise, can offer a profitable and intelligent pathway to a brighter business and environmental future. Carbon is cash, and reducing your output means retaining capital and growing profitability for the future.

So how is this achieved? Firstly, by fostering a different mindset when conceptualising sustainability measures. Data on utility usage can tell you when you’ve used more or less, but this aggregated data doesn’t have the granularity to explain why. While this is fine for quantifying and reporting on consumption to participate in a carbon exchange, this approach offers no mechanisms to improve these figures. But it doesn’t have to be this way.

Success and Sustainability

Novotek Solutions delivers operational technology with a methodology shaped by a deep knowledge gained in over three decades of experience in IT domains.

We’ve led the way in delivering all our projects to a high, IT-compliant standard. Our solutions are supportable, maintainable, and extensible to keep your operation fit for the future.

In decades past, manufacturers in various sectors have embraced initiatives focused on continuous improvement, aiming to enhance production yields, improve equipment reliability, and minimise waste in materials, labour, and capital. Advanced measurement systems that track metrics like machine downtime and material usage, leading to the establishment of comprehensive factory data infrastructures, all support manufacturers’ end goals.

These systems contextualise raw data by associating it with specific details such as order numbers and product codes. Advanced platforms like Proficy Plant Applications from GE Vernova can integrate data from primary sources like water flow meters into this contextual framework. This practice of collecting detailed data related to core equipment and products results in a robust dataset, which serves multiple purposes:

1. Automating Environmental and Compliance Reporting: Using directly measured consumption data to create regulatory reports and calculate incentives.
2. Enhancing Carbon Accounting: With varying standards for translating energy consumption into emissions, having granular data allows for flexibility in reporting and adapting to evolving auditing requirements.
3. Incorporating Footprint Analysis in Continuous Improvement: Analysing measured environmental factors alongside traditional performance metrics reveals the interplay between operational changes and environmental impact. Comparing a product’s footprint data across different times or locations helps identify significant variations.

This approach allowed a major North American brewer to spot cases where energy consumption varied when all other factors were equal. Measuring energy consumption next to production orders meant it could hunt for root causes through its efficiency management system.

Root causes for relative spikes in usage ranged from inefficient process control algorithms for heating or chilling equipment, inconsistent adherence to recipe setpoints, and poor power management relative to down or idle times. The brewer utilised this insight to make recipes and procedures consistent across all sites.

The result? The brewer met a 5-year energy-savings target in just three years!

Operator Behaviour, Transparency and Compliance

As more firms conclude that a functional information strategy is a critical first step in their sustainability journey, gaining the correct capabilities to gather and process data is essential. In times gone by, multiple data collection regimens assembled reports for different purposes, such as customers or regulators, which led to inconsistencies and undue workload on operators and analysts.

The alternative is a single data platform that serves multiple stakeholders, such as GE Vernova’s Plant Applications. Through a single platform, data is gathered once at an appropriate resolution, and the same data can then be repacked for multiple purposes.

Through this method, operations can automate the management and delivery of regulatory data. Adherence to future carbon passport schemes also becomes a process through which you already have the tools to deal with.

Turning to transparency, increasingly, customers are willing to pay a premium for ‘green’ products, where you can demonstrate a complete genealogy and the positive credentials of your products in total confidence. With a comprehensive data platform in place, you have the power to track and demonstrate the exact journey a product has gone through, from raw materials to finished goods. And that is not to overlook the power of transparent data on your operation.

With greater process visibility, automated with real-time data collection, operations gain the insight required for intelligence decision-making from the shop floor to the top floor. Ingesting and utilising this data with a powerful analytics platform drives an understanding of the cause-and-effect relationships between asset performance and input consumption. This granular data is then fed into corporate EHS and carbon accounting systems, allowing true utility cost profiles to be a part of production costing and planning exercises. Manufacturers then use cross-plant metrics to accelerate best-practice identification and dissemination.

But that’s not where it ends; by embedding analytics into control and visualisation programs, operators can be presented with rich information to drive decision-making at the shopfloor level. By using intelligent systems in this way, operations can also ensure they are not held hostage to the availability of specialists.

Innovative Strategies in Sustainability

To demonstrate how adopting a manufacturing execution system can offer a ‘many birds for one stone’ solution, we can look at the capabilities and conditions of an operation both before and after implementation.

Before

Without a detailed understanding of how changing utility inputs will affect processes, efforts to be ‘green’ can cause efficiency and material losses while also potentially introducing quality or product safety risks.

The differences between equipment and processes also present difficulties in formulating an effective strategy. With better data collection, all elements of variability can be profiled – including materials used in processes.

After

Data-driven decision-making brings cost, quality and carbon footprint into balance. With the confidence to act backed by information, tuning processes and utility infrastructure ensures sustainability efforts do not compromise operational performance.

The root causes of overconsumption are more easily understood, and strategies to mitigate them can be formulated and actioned at pace.

The ‘Many Birds’ at a Glance

If we’ve demonstrated anything in this article, we hope it’s the broad scope of what’s possible when looking to drive sustainability – and reap the real rewards on offer for manufacturing! Here are the key takeaways of what’s on the table as we progress towards environmental goals:

1. Expose hidden relationships between production and sustainability factors.
   • A single MES solution provides insight into materials, recipes, assets and processes to find the root causes of the overconsumption of utilities.
2. Gain a single source of truth and improve the visibility of your consumption.
   • Granular data gathered by the single platform can be packaged, analysed and presented to serve many needs.
3. Integrate metrics and analysis to provide additional insight.
   • Automating analytics within a single, scalable platform provides value from the shop floor to the top floor and drives fast, accurate decision-making powered by information.
4. Automate regulatory compliance and power transparency and traceability.
   • Gain competitive capabilities to demonstrate green credentials to customers and other stakeholders.

Last but not least, and in a nutshell, why select Plant Applications from GE Vernova?

• Flexibility in Data Management: The platform can easily link basic time-series data from meters to a wider range of elements like materials, products, and events, all through straightforward configuration.
• Support for Multiple Stakeholders: Plant Applications offers a variety of reporting and analytics capabilities, catering to both internal stakeholders focused on improvement and external stakeholders, ensuring their diverse needs are met.
• Open and Layered Approach: Unlike many sustainability metrics systems that are manual or limited to specific sensors, Plant Applications enhances existing sensor, automation, and software investments, offering a more integrated solution.

Continue the conversation

Do you have any questions about sustainability and manufacturing? Chat to one of our friendly experts to find out more.

A vital convergence

Cybersecurity is a crucial concern. OT equipment has become more IT aligned by necessity through standard protocols and ethernet/IP connectivity. Like a bucket of cold water, this fact woke the IT world to the significant vulnerabilities presented by connected operational systems. Furthermore, the press has continued to fill with stories of backdoors exploited by nefarious actors and the dire consequences of which to reputations, service, and profitability.

It was time for OT to be taken seriously and become part of the IT estate with the same high standards and best practice approaches to security.

So, what does this mean for you as a manufacturer?

Firstly, you must ensure that your control systems, such as PLC, SCADA etc., are secure from threats by keeping systems up to date and only providing connectivity between systems that require it. Leaving your entire operation wide open, with everything connected to everything else, is particularly hazardous. The optimal solution is to establish communication channels secured via switches and routers, allowing protocols to be enabled and disabled as required. Through this method, you can install firewalls between departments to further mitigate the threat of a cybersecurity breach.

The second point to consider is access control. Users should only be granted permissions to systems they require within an IT-supported domain. Paired with appropriate password complexity, a policy of regularly changing those passwords can minimise a potential vector of attack.

Next is virtualisation. By abstracting OT systems from the IT hardware, you can install physical hosts in an environmentally controlled data centre; rather than the old method of putting server racks under desks in control rooms, where they were subject to dust, heat, and the occasional accidental kicking from a steel-toe-capped boot.

Rounding out this brief overview is patching and backups. Patching regularly, at the same frequency as IT systems, ensures systems are constantly kept up to date and reduces the impact of ‘timely’ vulnerabilities such as Log4j. We still visit sites where Windows XP, NT and Server 2000 are still in use. These operating systems are running long after official support has ended, meaning security patches are no longer available and the vulnerabilities are well known and widely published.

Because OT should now be firmly on your IT department’s radar, creating a thorough backup regime will mean your systems are recoverable in the event of data loss due to a ransomware attack, operator error or any other disruption.

Experience and Expertise

Novotek Solutions delivers operational technology with a methodology shaped by a deep knowledge gained in over three decades of experience in IT domains.

We’ve led the way in delivering all our projects to a high, IT-compliant standard. Our solutions are supportable, maintainable, and extensible to keep your operation fit for the future.

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If you’ve walked through factories and seen operator or supervisor screens like the one below, you’re actually seeing both the best and worst aspects of technology evolution! Clearly, no data is left hidden within the machine or process, but screen design looks to have been driven by the abililty to visualiase what’s available from the underlying controls, rather than a more nuanced view of how to support different people in their work. you could say that the adoption of modern design approaches to building a “good” HMI or SCADA application has lagged what the underlying tools can support.

In Proficy iFIX, GE Digital has incorporated a mix of development acceleration and design philosophies that can both lead to more effective user experiences with a deployed system, while also making the overall cost of building, maintaining, and adapting a SCADA lower.

Three critical elemetns stand out:

1. Model-centric design

This brings object-oriented developement principles to SCADA and related applications. With a “home” for standrad definitions of common assets, and their related descriptibe and attribute data, OT teams can create reusable application components that are quick to deploy for each physical instance of a type. The model also provides useful application foundations, so things like animations, alarm filters and so on can be defined as appropriate for a class or type – and thereofore easily rolled out into the screens where instances of each type are present. And with developments in the GE site making the model infrastructure available to Historain, analytics and MED solutions, work done once can defray the cost and effort needed in related programs.

Taking advantage of what current-generation iFIX offers will mean a different development approach – considering useful asset and object model structure, then templating the way objects should be deployed is a new starting point for many. But with that groundwork laid, the speed to a final solution is in many (most!) cases, faster than older methodologies – and that’s beofer considering the advantage of resuability across asset types, or across multiple servers for different lines or sites.

Recovered time buys room for other changes

With rich automation data mapped to the model, and faster methods to build and roll out screen, different users can have their views tailored to suit their regualr work. Our earlier screen example reflected a common belief that screen design is time-consuming, so best to put as much data as possible in one place so that operators, technicicans, maintenance and even improvement teams can all get what they need without excessive development effort. But that can mean a confused mashup of items that get in the way of managing the core process, and in turn actually hamper investigations when things are going wrong.

But where development time is less of a constraint, more streamlined views can be deployed to support core work processes, with increasing levels of detail exposed on other screen for more technical investigation or troubleshooting. Even without fully adopting GE Digital’s Efficient HMI design guidelines, firms can expect faster and more effective responses form operators and supervisors who don’t have to sift through complex, overloaded views simplu to maintain steady-state operators.

With significant gains to be had in terms of operator responsiveness, and effective management of expectations, the user experience itself can merit as much consideration as the under-the-bonent changes that benefit developers.

Greenfield vs. Brownfield

It may seem like adopting a model-based approach, and taking first steps with the new development environments would be easier on fresh new project, whereas an upgrade scenario should be addressed by “simply” porting forward old screens, the database, etc. But when you consider all that can be involved in that forward migration, the mix of things that need “just a few tweaks” can mean as much – or more – work than a fresh build of the system, where the old serves as a point of reference for design and user requirements.

The proess database is usually the easiest part of the configuration to migrate forward. Even if changing from legacy drivers to IGS or Kepware, these tend to be pretty quick. Most of the tradeoffs of time/budget for an overall better solution are related to screen (and related scripting) upgrades. From many (many!) upgrades we’ve observed our customers make, we see common areas where a “modernisation” rather than a migration can actully be more cost effective, as well as leaving users with a more satisfying solution.

Questions to consider include:

While there is often concen about whether modernisation can be “too much” change, it’s equally true that operators genuinely want to support their compaines in getting better. So if what they see at the end of an investment looks and feels the same way it always has, the chance to enable improvements may have been lost – and with it a chance to engage and energise employees who want to be a part of making things better.

Old vs. New

iFIX 2023 and the broader Proficy suite incorporating more modern tools, which in turn offer choices about methods and approahces. Beyond the technical enablement, enginerring and IT teams may find that exploring these ideas may offer benefit in areas as straightforward as modernising system to avoid obsolescene risk to making tangile progress on IoT and borader digital initiatives.

Since the beginning of the COVID-19 pandemic, businesses across the UK have faced a surge in cybercrime. In fact, research indicates that UK businesses experienced one attempted cyberattack every 46 seconds on average in 2020. Industrial businesses are a prime target for hackers and the ramifications of a data breach or denial-of-service attack are far-reaching, making system security imperative. Here, David Evanson, corporate vendor relationship manager at Novotek UK and Ireland, explains how industrial businesses can keep their vital systems secure.

For many business leaders and engineers, it is still tempting to consider large multinational companies or data-rich digital service providers to be the prime target for hackers. However, the growing volume of cyberattacks on businesses globally show that any company can be a target of malicious attacks on systems and services.

According to research by internet service provider Beaming, there were 686,961 attempted system breaches among UK businesses in 2020, marking a 20 per cent increase on 2019. Of these attacks, Beaming noted that one in ten intended to gain control of an Internet of Things (IoT) device — something that indicates a tendency to target system continuity rather than conventional data.

Both factors together are cause for alarm among industrial businesses of all sizes. Hackers are targeting all manner of companies, from start-ups to global organisations, and focussing more on the growing number of internet-connected devices and systems that were previously isolated.

The consequences of a device being compromised range from data extraction to service shutdown, and in any case the financial and production impacts to an industrial business are significant. There is no single quick fix to bolster cybersecurity due to the varying types of hacks that can take place. Some cyberattacks are complex and sophisticated; others less so. Many attacks on devices tend to fall into the latter category, which means there are some steps industrial businesses can take to minimise risk.

Novotek has been working closely with industrial businesses in the UK and Ireland for decades. One common thing that we have observed with automation hardware and software is that many engineers do not regularly upgrade software or firmware. Instead, there is a tendency to view automation as a one-off, fit-and-forget purchase. The hardware may be physically maintained on a regular schedule, but the invisible software aspect is often neglected.

Older firmware is more susceptible to hacks because it often contains unpatched known security vulnerabilities, such as weak authentication algorithms, obsolete encryption technologies or backdoors for unauthorised access. For a programmable logic controller (PLC), older firmware versions make it possible for cyber attackers to change the module state to halt-mode, resulting in a denial-of-service that stops production or prevents critical processes from running.

PLC manufacturers routinely update firmware to ensure it is robust and secure in the face of the changing cyber landscape, but there is not always a set interval between these updates.

In some cases, updates are released in the days or weeks following the discovery of a vulnerability — either by the manufacturer, Whitehat hackers or genuine attackers — to minimise end-user risk. The firmware version’s upgrade information should outline any exploits that have been fixed.

However, it’s important to note that legacy PLCs may no longer receive firmware updates from the manufacturer if the system has reached obsolescence. Many engineers opt to air-gap older PLCs to minimise the cybersecurity risk, but the lack of firmware support can also create interoperability issues with connected devices. Another part of the network, such as a switch, receiving an update can cause communications and compatibility issues with PLCs running on older versions — yet another reason why systems should run on the most recent software patches.

At this stage, engineers should invest in a more modern PLC to minimise risk — and, due to the rate of advancement of PLCs in recent years, likely benefit from greater functionality at the same time.

Firmware vulnerabilities are unavoidable, regardless of the quality of the PLC. At Novotek, we give extensive support for the Emerson PACSystems products that we provide to businesses in the UK and Ireland. This involves not only support with firmware updates as they become available, but also guidance on wider system resilience to ensure that businesses are as safe as possible from hardware vulnerabilities. The growth in cyberattacks will continue long beyond the end of the COVID-19 pandemic, and infrastructure and automation are increasingly becoming targets. It may seem a simple step, but taking the same upgrade approach to firmware that we do with conventional computers can help engineers to secure their operations and keep running systems safely.

For years, digital transformation has been considered a new frontier for manufacturing and industrial operations. In the wake of the COVID-19 pandemic and the series of subsequent supply chain struggles, it’s becoming apparent that digital transformation is no longer the next frontier; it’s the next normal. However, it is also a journey rather than a destination. As with any journey, you need to know where you are departing from, not simply where you intend to go.

The 2021 State of Manufacturing report by Fictiv identified that the pandemic has accelerated interest and investment in digital transformation. 91 per cent of manufacturing business leaders increased their investments into digital transformation in the past year, with 77 per cent reporting to have done so substantially. Beyond the 91 per cent that have already ramped up investment, an additional four per cent agreed that digital transformation is essential to future success.

There are many possible reasons for why the extra four per cent have not increased their investments. One of the most common reasons that we encounter is uncertainty:  where to invest, what the benefit could be or whether the implementation will align with longer-term objectives. In many cases, it’s a reflection of business leaders not knowing their level of digital maturity or where they are in the digital transformation cycle.

Assessing your level of digital maturity and readiness is an essential step prior to undertaking any digitalisation project. Although they sound similar, digital maturity and digital readiness are distinct; the former focusses on technological deployments, whereas the latter encompasses a review of enterprise-wide processes, skills and staff.

Most manufacturers tend to focus on digital maturity as the sole measurement. This impedes the effectiveness of digital transformation initiatives. However, it is still an important metric to track.

Many manufacturers that Novotek encounters are around level two in the digital maturity index but set their project objectives on leaping to levels four and beyond. This leads to expensive, ineffectual system deployments that could be avoided with an accurate view of digital maturity and proper consultation. It is important that business leaders think of the index as an elevator; they must ascend one level at a time.

Digital readiness

Transformation does not happen in isolation. Assessing digital readiness involves looking at each aspect of a business to determine whether the foundations are in place for the next level of digital investment to be successful.

There are five assessment areas for digital readiness:

Whether assessing digital readiness or maturity, the most important factor is the honesty of the organisation. Assessments should be conducted on as much tangible, observable evidence and data as possible to produce an accurate reflection of its current state. In many cases, involving a specialist as a neutral third party is advantageous at this stage because it limits biases or accidental omissions and oversights.

Digital transformation appears to be an essential aspect of the next normal for manufacturers. Business leaders must be able to embrace it effectively to recover from and adapt to a post-COVID world.

In the age of connectivity, there is no shortage of useful information that engineers can leverage to optimise and improve operations. Everything from the speed of motors to the weather forecast can influence production. However, bringing these data sources together in a secure way is a challenge faced by many engineers. Here, George Walker, managing director of Novotek UK and Ireland, explains how engineers can bridge the gap between local process data and external data sources.

The Internet of Things (IoT) may still be a relatively new concept for many consumers and professional service businesses, but the idea of machine-to-machine communication and connectivity is nothing new for industry. In fact, it’s been more than 50 years since the programmable logic controller (PLC) first became popular among industrial businesses as a means of controlling connected systems.

The principle behind the PLC is quite simple: see, think and do. The controller will ‘see’ what is happening in a process based on the input data from the connected devices and machines. The PLC then processes this input and computes if any adjustments are required and if so, it signals these commands to the field devices. Traditionally, the field devices that could be controlled was limited, but recent developments in sensor technology have made specific components and resources much more measurable.

For example, if a water tank is almost at full capacity in a food processing plant, data from connected sensors can feed that information to a PLC. The PLC then sends the signal for the valve to close once the water volume exceeds a certain threshold, which prevents overflow. This is a simple control loop that sufficiently meets the need of the process.

Unfortunately, even as edge computing and PLC technology has advanced and offered more sophisticated data processing and control at the field-level, many plant engineers continue to setup their devices in this way. In reality, modern edge devices and industrial PCs (IPCs) are capable of providing much greater control, as well as responding to external commands or variables that were previously beyond the scope of control systems.

The outer loop

While the idea of the Industrial IoT (IIoT) is predominately a means of branding modern connectivity, the wider Industry 4.0 movement has brought with it some valuable advancements in edge and PLC technology. Among these advancements is the potential for on-premises automation and control systems to not only connect with local devices in an inner loop, but to draw from external sources: an outer loop.

The outer loop can take several forms, depending on what is most applicable or relevant to a process or operation.

For example, some more digitally mature businesses might have outer loops that feature an enterprise resource planning (ERP) system, supply chain management software or a wider manufacturing execution system (MES). These systems will share and receive relevant information or send required adjustments — such as due to raw material intake or low stock — to an edge device, which feeds into the inner loop. This allows industrial businesses to make use of more comprehensive data analysis than can be achieved in local data systems.

Alternatively, an outer loop could draw from data sources that are completely external to a plant’s operations. For example, a wind farm operator could use an outer loop that drew from sources of meteorological data for wind forecasts. This could inform the optimum pitch and yaw of a turbine, controlled by a field device.

Another example, and one that will resonate with many industrial businesses, is energy price. The cost of power from the electrical grid fluctuates throughout the day, which might mean that on-site generation — such as solar panels or heat recovery processes — become more economical during times of peak grid demand. An outer loop can communicate this data efficiently to the relevant systems in a business, and changes can then be enacted that allow the business to reduce energy costs.

Establishing secure connection

Clearly, there is a benefit for industrial businesses to establish both inner and outer loops. However, there is one barrier to deployment that most engineers encounter: hardware limitations.

Traditional PLCs were designed in a rather utilitarian manner to complete control functions effectively and in a straightforward manner. This no-frills approach persists even with modern PLCs — even with today’s technical specifications, most PLCs are not designed in a way that struggles to handle much more than a real-time operating system and some control applications.

Attempting to set up such a PLC to interact with an outer loop would either not work at all or severely hinder performance and risk failure.

Engineers can tackle this problem by introducing a separate gateway device that serves as an intermediary between the outer loop and the inner loop. However, this is a somewhat inelegant solution that requires investment in additional devices, which will require ongoing maintenance and introduce yet another device into already large system networks. Across an entire site, this quickly becomes costly and complicates network topologies.

A better solution is an unconventional one. It is possible to set up a modern automation controller in such a way that it breaks the conventions of PLCs, as long as the device is capable of multi-core processing at pace. From Novotek’s perspective, one of the best modern units that meet this need is Emerson Automation’s CPL410 automation controller.

The CPL410 can split inner and outer loop processing between its multiple processor cores. The inner loop and PLC processes can run from a single core, while another core — or even a group of cores, depending on complexity — can run more sophisticated containerised applications or operating systems. Additional cores can broker between the inner and outer loops, ensuring reliability and security.

A multi-core setup is useful because it allows the PLC processes and gateway to be consolidating into a single unit, without compromising performance capacity or speed. It also means that ageing or obsolete PLCs can be upgraded to a controller such as the CPL410 during any modernisation initiatives, minimising additional capital costs.

Although the idea behind the IoT is not a new one for industrial businesses, the fact that other sectors are embracing the idea means more external data points than ever before are available. With systems in place that can support effective inner and outer loops, industrial businesses can leverage the increased connectivity of external markets and enhance their own operations.

Food production is truly a sector that operates under the mantra of “reinvent the everyday, every day”. The sector is constantly evolving, whether manufacturers are innovating new product ranges that meet changing consumer tastes or switching packaging materials to extend shelf-life or reduce waste. And these are just examples of substantial shifts; food manufacturers are also regularly making smaller challenges by refining recipes, adapting processes or adjusting ingredient and material supply lines.

Despite — or perhaps because of — the environment of constant change, food processors can benefit more than many other manufacturers from carefully targeted use of data collection, visualisation and analysis solutions. After all, yesterday’s optimisation isn’t particularly optimal if today means a new stock-keeping unit (SKU), a new critical ingredient supplier or a new recipe.

The approach that many businesses take to becoming data-driven is to extensively map out their digitalisation journey, with each aspect comprehensively planned. This doesn’t generally support the flexibility needed in food manufacturing.

Rather than taking this approach, modern solutions make it possible to build or buy micro-applications that share common data infrastructure and even app-building or visualisation tools. This means that impactful new capabilities can be adopted through fast initial works that create re-usable building blocks. Later works then become incremental, rather than potentially having different systems creating overlapping capabilities.

Micro-apps in practice

We can see how this micro-app approach can be put into action by considering one of the most common challenges in food processing: managing the effect of variability in key ingredients, so that yields are maximised with minimal re-work or ingredient waste. It’s likely that a manufacturer would already have some of the information needed to address the challenge. The question is, how can you quickly supplement what’s in place?

It’s a safe bet that the factory has automation and maybe supervisory control and data acquisition (SCADA) systems, so there is an abundance of machine-generated data to tell us about the details of how processes are performing. Focussing more closely on yield performance, we can assume our manufacturer has a lab system where in-process and finished good tests give very clear indicators of how well a product is being made.

From Novotek’s experience, the most common gaps in tackling yield issues come from two areas. The first is supplier quality data, which is often provided either written down or in an electronic format that doesn’t mesh with existing systems. This makes analysis more difficult, because there’s no actual database to work from.

The second area is that the variations in raw materials that affect yields may actually be within the specifications defined for those materials. As such, there may not be an obvious fix. It’s likelier that material data needs to be analysed alongside several process performance and quality performance data points. Understanding the relationships between more than two or three variables will probably mean adding a new kind of analysis tool.

Micro-apps can be highly focussed on the core capabilities required. In this case, the micro-app would provide three core functions. First, it would provide a simple means to capture ingredient quality data as it’s received, into a system that also holds the specific material characteristic specifications and limits – all on a “by-lot” basis. It would also offer a machine learning tool that can help clarify how the range of material quality variation can be managed in relation to what machine settings or recipe adjustments might allow for good final yield and quality results.

Finally, the micro-app would be able to alert production staff to make recommended changes to a recipe or process as different raw material lots are staged for use – an automated monitor of yield/quality risk from material variation. This could be as simple as a new smart alarm sent back to existing SCADA, or a notification on a smartphone.

Industrial software vendors are adapting their offers, in recognition of the trend towards micro-apps aimed at specific business processes. So, the software licensing needed to enable material data collection and quality specification monitoring on a key process would be built around a low user count and narrow set of underlying configuration and integration points, rather than a comprehensive plant-wide project. That can mean starting investments in the low thousands for software and some deployment work.

Some of Novotek’s customers are now progressing through projects defined by such very specific functional needs. Our job at Novotek is to ensure that any new solutions serve the purpose of being able to act as supplements to other such micro-apps in the future.

Next stages

A strategic advantage of micro-apps is that the planning and execution stages are less time-intensive than a far-reaching, plant-wide digitalisation project. Food engineers can do several things to begin reinventing their everyday processes. For example, food manufacturers can deploy predictive downtime applications on key processes. These are apps that can even take into consideration whether the products made have their own impact on failure modes.

Each micro-app reflects an opportunity to make the overall food manufacturing operation more adaptable. This means that innovation in products, processes and business models can be done, all the while knowing that refining and optimising the “new” won’t be held up by tools and practices that are too difficult to adapt from the “old”.

The best approach may be to let the data dictate where to focus your innovation efforts. Or, if there’s a lack of useful data, then that itself may be the answer.

In this whitepaper, Novotek UK and Ireland explains how utilities operators can get to grips with data management to create an effective data-driven approach to innovation. Covering how to consolidate and modernise assets for data collection, how to make sense of utilities data and which method to use to get the most long-term value from data, the whitepaper is an invaluable resource for utilities operations managers and engineers.

Complete the form below to receive a copy of the whitepaper.

Complete the form below to receive a copy of the whitepaper.

In the past 12 months, the food industry has been forced to re-evaluate and re-assess its operational priorities. For years, many manufacturers focussed on flexible production to enable diverse product lines and mass customisation, in line with shifting consumer demands. In 2020, this was forced to change, and production efficiency and operational adaptability became the focus. Once more, automation and digital technologies came to the forefront of food manufacturing priorities.

Digitalisation is a word that has been banded around a lot in industrial markets for the past few years, serving as a catch-all phrase encompassing everything that generates, records and communicates data. Unfortunately, as with most amorphous phrases, this leads to confusion among managers about how to introduce these technologies, which causes costly errors in implementation, such as overlapping data collection systems or introduction of technologies that do not serve a strategic purpose.

For food manufacturers at the beginning of their digitalisation journey, the first step is to define an agreed and important goal, which the company can reverse engineer a solution from. Whether looking to deliver on a continuous improvement object that has been identified as part of a formal process, or just illustrating the value of an engineering team unleashed with time to think, it’s key to let the desired improvement dictate what kind of digitalisation will be needed.

For example, if material costs are too high and the agreed goal is to reduce them, a digitalisation project should establish systems that identify the factors influencing this. Understanding the root causes for yield problems could require a combination of machine data, ambient condition data, quality or lab data and information about material quality provided by suppliers. Thinking through where data is readily available, versus where it’s trapped in paper, spreadsheets or isolated automation, will ensure the plan can deliver on the purpose.

Planning at the outset of investing in digitalisation, but some food manufacturers may will have undoubtedly already rushed into digitalisation in years past. For businesses with some digital or automation technologies in place, one of the most valuable things to do is review the lay of the existing digital landscape. The easiest approach to doing this is to apply the ‘three Rs’ to your existing data: reduce systems overlap, reuse data and recycle data.

Reducing data collection system overlap not only makes it easier for managers to identify the source of a specific data set, it also streamlines costs. Why have a downtime system collecting machine event data, a yield analysis system collecting overlapping data and a work in progress tracking system that is separate to both of those? Having three systems collecting fundamentally the same data means duplicated configuration and deployment costs, as well as possible conflict over which one holds the ‘truth’.

An effective data and digitalisation strategy should also aim to use collected data in various calculations to produce several insights. For example, the downtime event data collected for OEE calculations may be part of what’s needed to solve a quality problem. The energy and water data collected for sustainability reporting may hold the key to real savings opportunities. Wherever there is a connection to a data source, managers should think of ways to make sure that a data point only needs to be collected once in order to be used many times.

Finally, offline analysis tools and some of the new analytics packages on the market could mean that old data offers recurring value as a firm chases finer and finer points of improvement. So, it’s important to set up a data management approach and data management platforms that can give you the option of making repeated use of data.

Digitalisation projects can lead to more innovative and effective ways of working for food manufacturers, but they rely on careful planning and strategic implementation. By giving full consideration to the goals to be reached or how data is used within a site, food businesses can ensure their systems are always effectively aligned with their goals.