The challenges facing today’s factory managers and optimizing workforce capabilities
Digitalization of the factory floor and how it supports the development of an agile workforce
The benefits of an agile workforce within the manufacturing industry
The digitalization of the factory floor and its support for Industrie 4.0 strategies is expected to fix a multitude of challenges that the industrial sector faces. One of these challenges is developing and managing an agile workforce to deal with operational changes. The agile workforce is expected to be dynamic enough to deliver the benefits associated with digitalization.
The common challenges factory workforces face
The manufacturing industry is going through diverse challenges associated with a changing global supply chain and the fallout from a pandemic. Although these challenges have affected the growth of the industry, immediate challenges within the factory are what keep facility managers awake.
Internal challenges such as an aging workforce and the need to work with limited resources to meet high consumer satisfaction levels continue to affect productivity. In the first case, the generation which has manned assets on the shop floor for decades is retiring, and with them goes the tribal knowledge associated with specific manufacturing processes. The demands for improved product quality from end-users alongside the implementation of lean manufacturing strategies mean operators are expected to optimize the use of available resources.
Fluctuating demand also creates a set of challenges for the factory owner. Increased demand generally means more operators or manufacturing equipment will be required to expand production activities. In certain situations, the capital resources to pay for extra labor or purchase additional equipment may be nonexistent. In such cases, optimizing workforce schedules to deliver agility becomes the more affordable option for meeting increased demand.
For example, if (the effect of) retiring workers reduces the workforce strength of an industrial enterprise by 20% and steep production deadlines must be met, an agile workforce should be able to pick up the slack with some restructuring. In this scenario, a means to identify operators who have the skill sets to operate more than one type of workstation equipment must be developed. Once vetted, multi-skilled operators can then be assigned across the assembly line to reduce the effect of operator shortages.
Vetting the skill sets of a multi-skilled operator and redeveloping a working schedule to accommodate these operators require extensive analytics. Paper analytics may have served adequately in the past – after a fashion – but costs can become burdensome with medium or large workforces. Thus, better analytical tools are required for workforce agility, and this is where digital transformation comes into the equation.
Digitalization of the factory floor and its workforce
The digitalization of the factory floor involves the application of digital-technology solutions to capture both structured and unstructured data to develop data-driven solutions to problems. Applying digitalization to develop an agile workforce is a continuous process as it is expected to solve changing workforce challenges.
For example, a factory owner may need to optimize workforce strength to deal with increasing demand, while on other days the workforce needs to be optimized to deal with defective equipment on the shop floor that can cause unplanned downtime. While the solution to increasing demand may be an optimized schedule, the solution to unplanned risk factors will be risk-based schedules.
The digital technologies that enable workforce agility include transformation solutions such as simulation modeling and scheduling software, the digital twin, and workforce management applications. These software applications or platforms utilize shop-floor data for evaluations, so data-capturing hardware must be included as part of the tech solutions required.
Shop-floor data drives every Industrie 4.0 strategy, which is why digitalization focuses first on implementing data-capturing solutions. Captured data can then be applied to implement solutions such as predictive maintenance or, in this case, an agile workforce.
With the captured data, risk-based scheduling software can upgrade a facility’s reliance on weekly schedules to risk-based schedules which are updated in real-time. Risk-based schedules integrate constraint data such as machine downtime, unavailable operators, or increased demand in its analysis to produce optimized scheduling solutions. These solutions ensure the factory continues running at its optimal capacity to meet production deadlines.
The digital twin and simulation modeling platforms provide intelligent-object-based environments for answering what-if questions and evaluating real-time scenarios. Simulation modeling recreates the factory floor in its virtual environment, allowing simulations to be run to gain insight into the effect of factors affecting a workforce. Optimized results from these simulations can then be applied to mitigate these challenges.
The digital twin is a cyber-physical entity in which data is shared between the virtual digital twin and data-capturing/data-producing assets on the factory floor. Unlike simulation models, the virtual replica does not rely on historical data but uses real-time data. As a result, the effects of challenges can be evaluated in real-time and optimization results implemented within the factory floor as proactive measures to forestall downtime.
The benefits of workforce agility enabled by digitalization of the factory
The benefit of an agile workforce cuts across improving productivity to enabling innovation. Here, some of the more important benefits of workforce agility have been provided.
Increase productivity – The ability to dynamically assign a workforce to diverse tasks improves production cycles as a factory ensures it has its best hands working on projects that fit their skill sets. Matching square pegs in square holes is accomplished using a workforce analysis and management application. These applications record operator skill set, qualifications, and experience levels and match them against available roles.
Data-driven production schedules – Digitalization of production schedules reduces the margin of error associated with manual schedules and introduces greater flexibility into traditional weekly schedules. The ability to integrate real-time data when developing schedules optimizes productivity and provides better work-life balances for operators.
Extensive planning – Digital transformation solutions also enable factories to implement long-term planning into production cycles. By utilizing historical data, simulation modeling, and scheduling software, alongside inventory data, manufacturers can create risk-based schedules for annual production cycles.
Achieving flexible manufacturing also relies on the agility of a workforce. The digital transformation that delivers manufacturing agility can also be applied to enable workforce agility to optimize productivity and create conducive workspaces in harsh manufacturing environments.