8 wastes of lean in an Industry 4.0 factory. What the data will show and what you won’t see in the system

The 8 wastes of lean can be identified both on the shop floor and in production data. MES, SCADA, OEE or WMS, depending on the scope of implementation, can show downtime, growing WIP, non-conformities and material flow. However, they will not automatically explain why an operator makes an unnecessary movement, why a particular approval exists, or why knowledge about a recurring problem does not reach the right person. Data therefore shortens the path to the cause, but diagnosis still requires observation of the process.

For a production director, the Muda list is useful when it leads to a decision: where the waste occurs, what trace it leaves and what needs to change.

Taiichi Ohno described the seven classic wastes of the Toyota Production System: overproduction, waiting, transportation, overprocessing, inventory, unnecessary motion, and defects and rework. The Lean Enterprise Institute points out that the eighth waste, unused human potential, was added later as Lean evolved.

The 7 wastes of muda and the 8 wastes of lean, sometimes also referred to as the 8 wastes of muda, are therefore not contradictory classifications. The latter expands the former to include employees’ knowledge and skills. Muda means an activity that consumes resources without creating value for the customer.

Toyota describes TPS through two pillars: jidoka and Just-in-Time. In jidoka, an abnormality should be detected and the process can be stopped so that a defect does not move further downstream and its recurrence can be prevented. For digitalization, the conclusion is that automation should support a process that has been understood rather than preserve an unnecessary activity.

A review published in 2022 in Procedia CIRP compared eight categories of Lean waste with Industry 4.0 technologies, including IIoT, Big Data, cloud computing, autonomous robots and system integration. These industry 4.0 examplesshow links between technologies and reducing specific wastes rather than one system solving the entire problem. The table works in a similar way: it helps select data for analysis, but it does not replace diagnosis.

Among the 8 wastes of lean manufacturing, overproduction is deceptive because a local KPI can look good. A machine meets its plan while the buffer before the next operation grows. Toyota describes Just-in-Time as producing what is needed, when it is needed and in the quantity needed. Compare the workstation’s output with demand from the next process and WIP. MES or APS can help with synchronization, but poorly configured rules can preserve overproduction just as effectively.

Another of the 8 wastes of lean covers the time during which a machine, person, material or information does not move to the next activity. A system can record downtime precisely, but the PLC signal alone does not explain whether the cause was a lack of material, a failure, a changeover or a quality decision.

ISA-95 describes models and information exchange between control, manufacturing operations management and business systems. In Muda analysis, a technical signal therefore often needs to be combined with an order, product, batch or event cause.

When working with the 8 wastes of lean, measuring transportation or inventory alone is often not enough. WMS, RFID or RTLS can show the location of the material and its route, but they will not explain why that route exists.

A buffer before a workstation may grow because of an oversized batch, lower throughput in the next operation, failures or a quality problem. Compare WIP with cycle times, downtime, changeovers and the pace of adjacent processes.

The 8 wastes of lean also apply to information flow. If an operator enters a batch number into a form, a leader copies it into a spreadsheet, and later the same information is manually entered into ERP, integration has a clearly defined purpose.

If, however, the system automates three approvals even though none of them affects a decision anymore, the process will become faster, but the unnecessary step will remain. Before automation, you need to check whether the activity is necessary.

Not all 8 wastes of lean can be found on a dashboard. A PLC will not show that an operator walks to get a label several times an hour or searches for a tool. Here, workstation observation, a Gemba Walk or a spaghetti diagram is required.

The same applies to unused human potential. An operator may know the cause of a recurring failure, but that information may not reach a process engineer or maintenance. Digital Andon and a Kaizen workflow can improve reporting, but they do not replace talking to the people closest to the process.

The number of NOK items alone shows the scale of the problem, not its source. More insight comes from linking the quality result with a batch or item number, machine, recipe, production time and process parameters.

SPC, traceability, process sensors or machine vision help narrow down the analysis if the quality result can be linked to the right place and moment in the process. Traceability systems can connect product history with process and quality-control data in exactly this way.

A hypothetical example: a queue of semi-finished products keeps growing before a testing station. The previous operation meets its plan, so its result appears correct.

The test, however, is waiting for a quality decision. Some products return for rework, which generates additional transportation, while the previous workstation continues producing despite the lack of downstream demand. Inventory, waiting, defects and overproduction occur in one place.

This is precisely why the 8 wastes of lean need to be assessed across the flow rather than as eight independent checklist items.

A study published in 2023 in Quality Management Journal was based on three case studies of Swedish manufacturing companies automating Lean practices. The authors identified digital waste in the practices studied in connection with JIT, changeover automation and digital customer participation.

Three cases from one country do not show the scale of the phenomenon in Polish industry. They are, however, a useful warning when working on the 8 wastes of lean. Similar risks are worth looking for in data collected without a defined use, duplicated dashboards, alarms without an owner responsible for responding, or reports that do not influence a decision.

These examples translate the concept of digital waste into typical information processes in a plant rather than presenting a list taken directly from the study. Before adding a data source, determine what decision a user will make differently after receiving that information.

Start with one problem, for example growing WIP, rework, frequent downtime or a long order lead time. Define where the waste occurs and what data can confirm it.

Check whether the information is already available in the PLC, SCADA, MES, ERP, WMS or quality system. Combine technical signals with production context and operator knowledge. Once the cause has been confirmed, you can decide whether to change the organization of work, integrate systems or automate.

Ownership of the problem should remain with the area responsible for process performance. IT and automation provide data and integration, but priorities result from production needs.

When working on the 8 wastes of lean, MES is useful when machine operation needs to be linked with an order, product, batch, operator or quality result. OEE helps analyze availability, performance and quality, WMS supports material flow, and SCADA shows process status.

The explitia Production Portal enables, among other things, order registration, OEE monitoring, reporting, traceability, process data collection and ERP integration. The scope of the solution can be expanded in stages, starting with a selected production area.

The 8 wastes of lean still describe problems known from classic manufacturing. Digital systems have primarily changed the ability to measure them, connect the data and narrow down causes faster.

A project should therefore start with a specific waste, a process owner, available data and a measure of the result. Only then can you assess whether MES, OEE, SCADA, WMS, integration or a change in the organization of work is needed.

The 8 wastes of lean are overproduction, waiting, transportation, overprocessing, inventory, unnecessary motion, defects and rework, and unused employee potential. The first seven are associated with Taiichi Ohno’s classic list, while the eighth was added later.

The original classification associated with the Toyota Production System included seven wastes. Unused employee potential was added later as Lean evolved.

No. OEE focuses on availability, performance and quality. It does not directly describe, among other things, unnecessary transportation, employee motion, excess inventory or unused team knowledge.

No. Research describes digital waste, meaning digital activities that do not create value. Automation can therefore also accelerate a process that contains unnecessary steps.