Smart data, artificial intelligence and self-learning machines are giving mechanical engineering an enormous boost on their way towards the Smart Factory and Industry 4.0. The fully automatic control and networking of machines are among the core tasks in many companies. ROI supports companies in machine and plant engineering in digitising their value chains, developing new business models, implementing operational excellence and designing the global footprint. ROI consultancy’s customers include leading companies in machine and plant engineering.
- Global footprint
- Network planning
- Site planning
- Development strategy per location
- Manufacturing and logistics
- Industrial digitization
- Industry 4.0/Lean digital
- S&OP blueprint for global SAP rollouts/process design for S/4Hana
- Smart services
- Digital transformation: see, for example, the Miele Case
- Innovation management
- Development process optimisation
- Standardisation and modularisation
Cost reduction/restructuring due to market changes
Sales successes secured pole position for a company in the plant construction and mechanical engineering sector. However, this was extremely at risk: a significant margin erosion with unchanged sales and well-established structures required major changes in a short period of time.
Reduce variance and complexity within the product portfolio in the highly specialised textile machinery construction market. Key objectives: Cost reductions and strengthening the position in the Chinese market.
One steel group working together with ROI implemented an OPEX strategy at almost 200 locations. The aim: use energy for change, not just freely but focused and result-oriented. To ensure that operational processes not just become better, but rather excellent.
Quality is not negotiable, regardless of complexity. To bring quality management to a new level, the right combination of proven measures and new technologies needs to be found.
Building a digital twin
One automotive supplier improved the transparency of work and organisational processes in its manufacturing plant for dashboards. The task was to identify and eliminate errors and efficiency losses with a high number of variants and at high speed.