ARUN BHATIA

As AI enters Process improvement initiatives , Let me share from my industry AI enabled Time motion study to reduce conveyor line downtime. From operational leadership perspective , MBB plays a critical role in ensuring AI delivers authentic and sustained improvements and ensure it strengthens improvement journey . As a MBB must own following things : Clarity of “Working time vs. non-working time”: Ensure AI differentiates true conveyor line working time from avoidable idle, motion , and diagnosis delays. Breakdown of work task : Convert AI insights into standardized work task for operators and maintenance staff to ensure seamless operations Expected response times: Define target times for fault response, repair, and restart—incorporated into daily management check sheet . As a MBB must challenge following things : Fallacious averages data : AI insights that hide variation across shifts, different models, or team with varied skill set. Tool-driven recommendations: Recommendations that optimize data patterns but ignore actual physical movements and access constraints. Operators Skill set : Faster operator motion that does not reduce overall line stop time. As a MBB must safeguard following things : Safety : No reduction in maintenance time that compromises safe access or lockout–tagout practices. Sustainability : avoid unrealistic cycle-time expectations for operators/team. Process ownership: Ensure improvements remain incorporated in standard work, not dependent on AI dashboards. As a MBB our job to ensure to leverage AI insights and convert them into smooth process flow and reliable machine availability and results in conveyor uptime to boost productivity ( PQSCDM approach ) P- Productivity boost Q- Sustain Quality ( Consistent product quality ) S- Safety C- Cost savings D- On time delivery M - Improved operators Morale