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Increase output. Reduce downtime. Operate with control.

We work with operations and maintenance teams to turn existing plant data into stable, measurable operational performance. For over 20 years, Accesa has supported manufacturers across Europe and the DACH region.
Two decades of manufacturing engagements, and the same operational challenges keep coming up. Now, with AI knocking at the door, the pressure to act on existing data has never been higher.
These recurring challenges shaped the four service areas we focus on today:
  • predictive maintenance
  • operational efficiency and OEE
  • quality intelligence
  • automation of manual workflows

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THE OPERATIONAL REALITY

In most manufacturing plants, the data needed to run operations already exists. Machines generate signals, downtime is logged, production and quality results are tracked, and maintenance work orders are created across SCADA, MES, ERP, and CMMS systems.

The problem lies in the effort required to turn that data into a shared, reliable view during daily operations. And when the plant doesn't have the right tools to use its data effectively, it runs into problems like:

Recurring breakdowns on critical assets

halting the production flow on the whole shop floor.

Late scrap detection

leading to more waste, higher rework rates, and faulty quoting.

Hidden performance losses

such as micro-stops and speed loss, visible only after the shift, not during.

OEE calculated differently across shifts

turning OEE into a reporting metric rather than a tool for daily decisions.

Decision latency between maintenance and operations

more time spent agreeing on what happened before deciding what to do next.

WHERE WE PARTNER TO REDUCE OPERATIONAL FRICTION

Predictive Maintenance

Move from reacting to failures to planning interventions before breakdowns occur, using the machine data you already have.

  • Detect anomalies early

  • Increase MTBF

  • Reduce unplanned downtime

  • Shift from reactive to risk-based planning

Validated in production environments with measurable downtime reduction.

Operational Efficiency

Increase output and operational stability by providing a shared, trusted view of performance and losses.

  • Standardise OEE definitions and loss taxonomy

  • Make availability, performance, and quality losses visible

  • Support daily and shift routines focused on top loss drivers

Validated where unified loss visibility reduced time spent reconciling numbers and enabled faster decisions during the shift.

Quality Intelligence

Reduce scrap, rework, and quality risks by detecting defects early and understanding process-level root causes.

  • Detect defects early

  • Analyse root-cause patterns

  • Improve First Pass Yield through parameter insights

Improved process stability, output, quality cost, and delivery performance without buying a single extra sensor.

Automation & Digital Workers

Reduce manual work, accelerate decisions, and ensure consistent execution across shifts.

  • Automate reporting and escalation

  • Leverage AI assistants for maintenance, quality control, and operations

  • Use digital workers to orchestrate multi-team workflows

Reduced manual coordination and faster escalation across shifts, with clear ownership at every step.

Stories from the Shop Floor

Predictive Maintenance

From Reactive to Proactive Reliability in Industrial Machinery through Predictive Maintenance

A predictive‑maintenance proof of concept enabled 53% early failure detection, supporting proactive reliability and reduced unplanned machine downtime.

Read more

Automation & Digital Workers

Increasing Consistency and Operational Efficiency by Automating Credit Risk Assessment Processes

Automated credit assessment reduced manual effort by over 90%, delivering faster, consistent decisions and enabling scalable, rules‑based operations.

Read more

Operational Efficiency

Improving Paint Shop Performance with Quality Analytics

Advanced quality analytics helped reduce paint‑shop rework and scrap by 20–40%, improving defect detection, process stability and overall equipment efficiency.

Read more

Automation & Digital Workers

Reducing Manual Effort through Centralised Control in Scientific Equipment Management

A centralised on‑premise platform unified user, device and data management, reducing admin effort by ~50% and standardising laboratory operations.

Read more

HOW WE WORK

Discovery

for alignment, solution design, and prioritisation. Understand your current plan setup, challenges, constraints, and success criteria. Cocreate the timeline. Timeline: 1 to 2 weeks Outcomes: Technical blueprint, KPI hypothesis

Start small

targeting operational improvements without disruption. Start with a limited scope: one line, asset, or clearly defined use case. Solve a current challenge with a small group directly involved in daily execution. Timeline: 4 to 8 weeks Outcomes: working solution, measurable impact

Scale

when ready. Only after teams see that the approach works in practice and fits their way of operating, we replicate across additional lines, assets, or plants. Timeline: 6 to 12 months Outcomes: rollout plan, operating model

Our Footprint

20+ years supporting manufacturing in DACH
Delivery hub in Cluj-Napoca
Regional presence in DACH and Nordics
Industry / Manufacturing / Hero

Don't let firefighting get in the way of improving your operational efficiency

Frequently Asked Questions

Do we need new hardware, sensors, or systems?
What if our data is incomplete, inconsistent, or spread across multiple systems?
How long does a pilot take, and what do you need from us?
Do you replace our MES, ERP, or CMMS?
Who owns and maintains the solution after the pilot?
How do you measure success?
How do you handle data security and access to production systems?

OUR EXPERTS

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Maria Irimias
Portfolio Service Manager - Data & AI, Hyperautomation, Intelligent Workplace

Technological Partners

Databricks
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Amazon
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CERTIFICATIONS

ISO 9001

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ISO 14001

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ISO 27001

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GET IN TOUCH

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WHAT HAPPENS NEXT?

1

After you submit a contact form on accesa.eu, one of our representatives will review the information and get back to you in 1-2 business days.

2

We will then assign a Technical Presales expert to have a deep dive and assess your requirements and objectives.

3

The Presales expert will work with a bid team and a Software Architect to prepare a high level project estimation and the Sales expert will provide you with a commercial offer.

We will get back to you within 1 to 2 business days. We will also provide a proposed project allocation and start date after a minimum of 15 days from the deep dive session.

Address: Constanta 12, Cluj-Napoca, Romania 

Phone number: +4989215485115