Production Process Integration Using Quota Fulfillment Probabilities
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Solution Overview
Problem
Inadequate information flow in industrial supply chains leads to demand fluctuations, resulting in idle inventory, re-planning of non-optimal production batches, and underutilized production capacities due to inefficient IT systems across different production levels.
Innovation Solution
A production process integrating method that identifies and measures physical parameters influencing production activities, determines probability indices for fulfillment times, and provides these indices to higher production levels, enabling better integration and optimization of production capacities across levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If separate production entities operate independently with traditional IT systems, then each entity maintains operational autonomy, but information flow becomes inadequate leading to demand fluctuations and inefficient production planning
Solution Approach 1:
The patent merges separate production entities into a unified virtual production capacity by integrating their IT systems through a common platform. This allows information from multiple production levels to be consolidated and shared, eliminating information loss while managing complexity through standardized integration protocols and centralized data management.
Solution Approach 2:
The patent implements a universal IT platform that serves multiple functions across different production entities and levels. This platform handles information collection, processing, sharing, and coordination simultaneously, improving information flow adequacy while avoiding the complexity of multiple separate systems through a single multi-functional solution.
2Reliability
If production entities accumulate inventory to buffer against demand fluctuations, then production stability is improved, but idle inventory and storage costs increase
Solution Approach 1:
The patent implements real-time feedback loops where production data from all levels is continuously collected and analyzed. This feedback mechanism enables dynamic adjustment of production plans based on actual demand signals, maintaining production stability without requiring large inventory buffers. The system responds to changing conditions immediately rather than relying on pre-stocked inventory.
Solution Approach 2:
The patent uses probability indices and predictive analytics to perform preliminary actions in production planning. By forecasting fulfillment times and potential disruptions beforehand, the system can proactively adjust production schedules and allocate resources efficiently, maintaining reliability while minimizing the need for excess inventory as a safety buffer.
3Adaptability or versatility
If production planning is frequently re-adjusted to respond to demand changes, then responsiveness to market conditions improves, but production efficiency decreases due to non-optimal batch sizes
Solution Approach 1:
The patent implements dynamic production planning where batch sizes and schedules are continuously optimized based on real-time data from the integrated system. Rather than fixed plans, the system adapts production parameters dynamically while maintaining efficiency through automated optimization algorithms that consider both responsiveness and productivity requirements simultaneously.
Solution Approach 2:
The patent changes key production parameters such as batch sizes, production rates, and scheduling intervals based on probability indices and fulfillment time predictions. These parameter adjustments are made systematically using the integrated information system, allowing the production plan to adapt to demand changes while maintaining optimal efficiency through data-driven decision-making rather than reactive re-planning.
4Reliability
If production capacities are expanded to meet peak demand, then ability to fulfill orders improves, but unused production capacities increase during low-demand periods
Solution Approach 1:
The patent implements dynamic capacity allocation where production resources are flexibly assigned based on real-time demand signals from the integrated system. During peak demand, additional capacities are activated; during low-demand periods, resources are scaled back or reallocated. This dynamic approach maintains order fulfillment capability while minimizing energy waste from continuously operating unused capacities.
Solution Approach 2:
The patent creates a virtual production capacity that pools resources from multiple physical production entities. This universal capacity can be allocated to different orders and products flexibly across the network, ensuring that order fulfillment requirements are met while reducing the need for each individual entity to maintain excess capacity for peak demand scenarios.
Data Source
AI summary
Multilevel production processes are integrated utilizing as input a relatively lower production level. Activities at the lower production level producing an end product and physical parameters that influence these activities are identified, the identified physical parameters are measured with sensors, and a quota fulfillment probability index for an activity is determined using the measured physical parameters. The quota fulfillment probability index is supplied to a production entity operating at a consecutive, relatively higher production level than the activities at the relatively lower production level.