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Scheduling Decision Process

It is crucial, but also very challenging, to generate an optimal production schedule that optimizes throughput while minimizing costs. With smart scheduling decision process, the impact of real-time production decisions on orders and forecasts can be shown. In disruptions such as machinery breakdown, a successful short-term production plan must be flexible enough to rapidly revise that schedule in response to sudden changes.

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Measurable Benefits

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Overall Equipment Effectiveness (OEE) Improvement

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Reduction in Operational Costs

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Reduction in Backorders

Measurable Benefits

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Net Profit Improvement

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Increase in OTIF performance

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Reduction in Inventory Costs

Customer centric detailed scheduling focuses on adapting operational decisions to recent real-life disruptions while gaining end-to-end visibility from shop floor to demand and assessing risks and opportunities.

Gain Visibility Over Goods

Instantly see the impact of each production decisions on customer orders and forecast in terms of shortages and tardiness.

  • Instantly see the order and forecast shortages, tardiness with respect to production decisions (pegging)
  • Alert notifications, bringing forward the impact of decisions
  • Gain visibility of short- term material, semi-finished and finished goods' stock projection with respect to production decisions (consumed material states (stock, purchase etc.) and allocated resource states)
  • Analyse the long-term and short-term inconsistencies (compare capacity decisions & scheduling decisions and notify if any inconsistency occurs)
Improve OTIF Performance
Improve OTIF Performance

Optimize Short-term Production Plan

Make the optimized short-term production plan by analysing your stocks, requirements and orders.

  • See instant results with Gantt chart
  • Gain visibility of resources
  • Shift & unavailability planning
  • Create a production plan easily with drag & drop
  • Multi-level scheduling (which can be extended to automatic scheduling)
  • See the impact of production decision via dynamic global pegging
  • Handle disruptions with real life constraints

Customer Cases

Automotive
80% Reduction in Response Time
Automotive

The challenge:

A company in automotive sector was not responsive enough to its’ customers because of its complex production network with different products, many layered BOM structure and a variety of route alternatives.

The outcome:

The company reduced their response time to customers 80% by delivering feasible due dates to new orders and adjusting their order sequence considering their constraints and priority preferences.

FMCG
10% Improvement in Overall Equipment Effectiveness (OEE)
FMCG

The challenge:

A company producing electronic appliances was frequently facing disruptions in their production flow. Because of the disruptions, they often had backorders, resulting in worsened customer experience.

The outcome:

After ICRON CCP, the company improved its overall equipment effectiveness (OEE) 10% by making feasible plans according to the due dates generated by ICRON CCP.

Customer Cases
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