Breaking down silos and unifying manufacturing systems with data integration

  • January 18, 2022

Recent PMI figures published at the end of August have revealed that manufacturers face a plethora of challenges in areas such as capacity constraints and supply chain disruption in the coming months. These issues are likely to impact the sector for an extended period of time as the global economy recovers from the pandemic.

While there is no overnight fix to these problems, there are ways for manufacturers to make themselves more efficient and resilient in the face of any challenge. To achieve this, there has been a shift to implement digital tools, with organisations now investing heavily in emerging technologies such as advanced robotics, IoT, artificial intelligence and machine learning capabilities.

The ultimate goal behind all of these new technologies is for manufacturers to transition from traditional factories to smart factories, where data is king and every aspect of production floor performance can be measured and scrutinised in real time. Also key to this is the ability for employees to “talk” to other logistic and finance departments.

Factories have relied on data to monitor performance for many years, but one of the biggest recent challenges has been how to properly manage the proliferation of new data sources. This is where effective data integration is key.

Data management headaches

There are a number of historical hurdles that have stood in the way of data integration. The first is the fact that data has not always been easily accessible. Secondly, data in the past would often be recorded on paper, or in Excel spreadsheets as digitisation began to take hold.

Finally, manufacturers have had to manage silos of different data in different places, many of which are visible to only a limited number of people. Take, for example, the disconnect between operations or productions data, and data produced by logistics or finance systems. These silos represent different sides of the business, and often there is very little meaningful integration between them.

This challenge is one of the most pressing, as the amount of data organisations now hold means there are more silos than ever before. There is now a constant need to collect, share and process huge amounts of data from machines, devices and production systems, which means finding a way to integrate all of this into a single, overarching system.

The present-day challenge

There are a range of challenges manufacturers face when collecting and harnessing vast amounts of data generated by modern organisational systems. A myriad of these have grown over time with little synchronisation between them, exacerbating the siloed data issue.

Systems such as ERP, MES, PLC, MED, QM, MM, PLM, SCM, and CRM all have different objectives and were introduced at different times, meaning they have largely performed independently from one another. While this worked decades ago, in smart factories it leads to data bottlenecks, making real-time analysis impossible. Simply transferring data from one system to another at the end of the day makes verification difficult, and does not provide the speed needed to produce actionable intelligence.

Data integration and its benefits

Fortunately, there are ways to overcome these challenges and achieve data integration. According to Gartner “the discipline of data integration comprises the practices, architectural techniques and tools for achieving the consistent access and delivery of data across the spectrum of data subject areas and data structure types in the enterprise to meet the data consumption requirements of all applications and business processes.”

Different solutions tend to focus on data either being collected from operations and productions systems, or through logistics and finance systems, while keeping these two business elements largely separate. True data integration combines these two worlds, allowing them to talk with one another. By doing this, the organisation as a whole will witness a plethora of benefits including improvement in production efficiency, agility and decision-making, as well as:

  • More accurate, timely data
  • Enhanced internal communication across the business
  • Reduced spending and time spent on tasks
  • More effective inventory management and forward planning
  • Machine repairs made easier
  • Focus the entire organisation on a well-defined, aligned set of KPIs
  • Improved overall equipment effectiveness (OEE)

To do this, manufacturers must formulate a data integration strategy and commit to it wholeheartedly. This should include a concerted effort to gain visibility and understanding of every system and data source, and work out what is making it so difficult to unify it all. The business must have a clear idea of what it wants to achieve through data integration, and should then implement the right tools that can successfully break down the silos and feed all data into a single dashboard.

Installed sensors on machinery are a good example of such tools. With these sensors in place, manufacturers can get access to real-time data covering a range of areas, including machine performance, maintenance requirements and whether production levels are in line with KPIs. This can then be automatically integrated with data collected by other sensors, and with other systems such as MES.

Enhancing internal operations

While it may seem complex at first, more manufacturers are now choosing to integrate their data because of the benefits it brings to their internal operations. One of the biggest advantages is it brings all major stakeholders into the decision-making process, from managers on the production floor, to those working in the boardroom. This improved flow of data therefore has a dramatic influence on business performance in the long run.

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