Real Results
CASE STUDY
We helped a leading biologics company reduce batch cycle times by 30%.
Smart Connected Operations delivers measurable business outcomes
- 10-15% reduction in tech transfer and scale-up timelines
- 10% OEE improvement
- 10-25% increased productivity
- 10-40% reduced maintenance cost
- 15-30% faster resource tracking
- 10-12% improved labor efficiency
- Faster time to market
We help manufacturers connect equipment, lines, devices and workers across the value chain and apply data science to enable smart connected operations.
With increasing regulatory scrutiny and market variations, ensuring continuous process and materials quality in pharma and biotech manufacturing is as important as ever. As gene and cell therapies push the industry towards personalized medicine, there is a need to bring new drugs to market in shorter times and smaller batch sizes while leveraging single use technologies. The margin for error or iterations is shrinking.
The legacy of siloed systems, data and operations inhibits innovators from meeting market and regulatory expectations.
Smart connected operations answers these challenges by leveraging digital technologies across product development, manufacturing, operations, supply chain, and logistics to increase connectivity. Establishing a digital thread across functions and applying data science enables the creation of site specific and enterprise manufacturing control towers across distributed facilities, lines and equipment. This generates real-time insights for faster and better decision-making, ensuring efficacy, safety and quality, and increasing efficiency across the extended value chain while also simplifying compliance and process validation.
This necessary shift represents more than just an approach to digital technologies. Smart connected operations is also a means of transforming the workforce. From connecting workers to more human-centric workflows, to shifts in company culture, humans are at the core.
How We Help Companies Build Smart Connected Operations
Our approach focuses on converging systems across the enterprise, applying data science and human centric process design to drive more throughput and gain real-time insights across the value chain. Putting the right information at the right time in employees’ hands helps them improve operational decisions and increases their job satisfaction.
In pharma and biotech, we commonly converge data from information technology systems such as ELN, LIMS, PKM, DKM, RIMS and others to MES, SCADA, DCS, PLC and sensors on the operational technology (OT) side.
Three Key Phases to Digitizing Your Operations
Mechanical to Digital
- Design, implement and deploy an IIoT platform
- Establish connected control system foundation
- Enable continuous improvement
Reactive to Predictive and Prescriptive
- Optimize manufacturing monitoring and control systems with machine learning and model predictive control (MPC)
- Improve manufacturing performance through predictive and prescriptive analytics
Organize to Scale
- Establish repeatable deployment playbook and operating model
- Develop knowledge and skillsets in the organization to scale capability across the facilities and manufacturing portfolio
Our Smart Connected Operations approach aligns with Pharma 4.0TM strategies and extends the associated smart factory investments and benefits.
Pharma 4.0TM is an operating model developed by the International Society for Pharmaceutical Engineers (ISPE) to adapt Industry 4.0 strategies, also called Smart Factory, to the unique requirements of the pharma industry. It aims at enabling organizations involved in the product lifecycle to leverage the full potential of digitalization to provide faster innovations for the benefit of patients.
Pharma 4.0TM is an operating model developed by the International Society for Pharmaceutical Engineers (ISPE) to adapt Industry 4.0 strategies, also called Smart Factory, to the unique requirements of the pharma industry. It aims at enabling organizations involved in the product lifecycle to leverage the full potential of digitalization to provide faster innovations for the benefit of patients.
High Impact Pillars of Smart Connected Operations in Pharma & Biotech
Product & Process Development
Digitalization of product, packaging, process and recipe development to improve technology transfers from the lab to clinical materials development through commercial drug product development and to accelerate scale-up across the manufacturing network.
Yield & Resource Optimization
Improve overall manufacturing productivity and resource allocation with optimization algorithms for labor, materials, lines and equipment planning and scheduling.
Manufacturing Simulation & Emulation
Design and validate manufacturing processes by authoring, re-using, simulating, and optimizing automation-design based on fully realistic kinematic behavior.
Process Control Optimization
Improve process control, production rate and product quality with prescriptive machine learning algorithms including soft sensors, lineside next best action, and model predictive control.
Production Performance Management
Drive OEE improvement and lean production management with centralized and localized manufacturing control towers powered by real-time metrics.
Asset Performance Management
Increase asset uptime and performance by leveraging AI to detect and predict faults, and prescribe mitigation activities.
Equipment & Line Commissioning, Changeover, Clearance
Enable centralized equipment support and maintenance, safer repair work, and rapid spare parts identification with augmented reality, computer vision and object recognition.
Energy Management & Sustainability
Achieve sustainability goals and improve the bottom-line with industrial IoT and advanced analytics, enabling smart facilities with real-time visibility, monitoring, analysis and control of energy, water, air, gas and steam.
Core Areas for Applying Digital Technologies to Enable Smart Connected Operations
Technology Transfer and Scale-Up
Continuous Process Validation (CPV)
Soft Sensors
Line Commissioning, Clearance, Changeover
Lineside Next Best Action
Yield Optimization and OEE Improvement
Manufacturing Control Tower
XR Augmented Weigh and Dispense Operations
Technology Partners
CASE STUDY
We helped a leading biologics company reduce batch cycle times by 30%.
Our client sought to improve the quality and performance of their production processes with real-time analytics insights.
Existing manufacturing processes were based on manual sampling methods resulting in extended batch cycle times and sometimes leading to scrap.
We deployed predictive models that assess real-time independent variables (inlet air temperature, exhaust air temperature, and fan speed) and dependent variables (ideal moisture level) with a machine learning model trained with historical performance data to continuously predict ideal moisture targets with 95% confidence.
Operators now have real time decision support model-based predictions for more reliable outcomes with improved batch cycle times.
Our work improved process control, production rate and product quality while reducing batch cycle times by 30% and scrap or waste by 5%.
Thought Leaders
