Improvement Twin
The Improvement Twin gives Production, Maintenance and Improvement teams clarity by identifying and measuring production bottlenecks in near real time, to enable prioritisation of work and improvements.
The Problem
Input and process variability are a fact of operational life, and production losses can occur for many reasons across a site. Some sites suffer from lingering or recurring production losses, while others achieve production targets but with excessive operational costs. The introduction of new equipment and processes always causes unintended changes, and commodity price fluctuations can force sites into different modes of operation at short notice. Large scale decarbonisation initiatives are just the next wave of deliberate change, and AI driven process change will follow shortly thereafter.
Prioritising improvements and changes of process are difficult without a global production loss measure. When local and global production losses are clear and measurable, across all connected value chains, then prioritisation and tradeoffs can be made, and teams can deal with change continuously.
The Improvement Twin is designed to give Production, Maintenance and Improvement teams clarity by identifying and measuring production bottlenecks in near real time, to enable prioritisation of work and improvements.
The Improvement Twin consists of a constraints model of your site or connected value chains, configurable dashboards to align to MOS requirements, and a tradeoff advisor to optimise initiative ROI or minimise production losses.
Situation
The Improvement Twin is applicable across 3 situations:
Increase Production
Reduce Operating Cost
Optimise Improvement Initiatives
Increase Production
Where sites seek to lift throughput and close the gap to nameplate production, the Improvement Twin provides targeting and continuous measurement of constraints that are creating production losses. By adding more data and enriching the constraints model, sites can increase automated near real time attribution of constraints.
Reduce Operating Cost
Where sites achieve production plans, but operating cost reductions are sought, the Improvement Twin provides visualisation of production loss / planned / unplanned work overlaps at each value chain. With a real time view of local production losses, and subsequent predicted buffer timings (e.g. 2hrs of buffer remaining), SIC processes can seek to optimise remaining shift time. Analysis of previous period production losses provides continuous improvement teams with data to optimise production/work planning and reduce avoidable losses.
Optimise Improvement Initiatives
Optimise production loss avoidance or initiative benefit-cost when targeting global production losses. Measure initiative success by reduction of production loss, rather than project cost/schedule. Persistently measure completed initiatives to ensure benefits remain locked in.
Solution
The Improvement Twin solution can be implemented in stages, based on the needs of each site.
Stage 1 provides the constraint model for measuring local and global production losses and targeting and measuring improvement initiatives, to increase throughput. Improvement initiatives are suggested based on measured production losses and recurrence of issues.
Stage 2 brings in work, fault, isolation and shutdown data to provide rapid attribution of production losses, and to enable re-prioritisation and replanning of work and production to increase throughput and/or decrease operating cost.
Outcomes
The key outcomes that the Improvement Twin enables are:
· Identifying where real bottlenecks appear and move across the day is the first step
· Maximising throughput by targeting tactical and SIC initiatives at the many moving bottlenecks
· Maximising throughput by targeting Improvement initiatives at the largest and recurring cumulative production losses
· Increasing maintenance productivity by re-planning work to take advantage of unplanned downtime or changes to production plans
· Allocating improvement budgets by production opportunity to better align cost with measurable throughput improvements
· Accelerating post shutdown ramp ups by identifying bottlenecks as they appear and move in near real time