Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Robust simulation software designed to enhance asset performance is available, offering features such as maintenance and spare parts optimization, availability assessments, reliability-centered maintenance strategies, life cycle cost analyses, and accelerated life testing, all within a single cohesive platform. This software seamlessly integrates with your SAP or MAXIMO systems for comprehensive data analysis. It allows for the identification of critical machinery and the automatic generation of failure models through Weibull analysis. By leveraging simulation, you can refine your maintenance strategies and cut expenses. Additionally, the tool predicts system availability while optimizing design processes. It also facilitates the simulation of capacity for multiple products, incorporating target cost penalties. You can model interdependencies within systems using reliability block diagrams (RBDs) or fault trees. Operational rules can be embedded to ensure accurate performance simulations. Furthermore, it helps in determining the optimal spare parts inventory strategy. Life cycle costs can be predicted, and the ALT module allows for the analysis of test data related to stressed failures. Lastly, the software enables the identification of performance trends within the process reliability module, providing valuable insights for continuous improvement.
Description
Advanced Process Control (APC) provides a highly efficient solution for enhancing your plant's performance without requiring any hardware modifications. By implementing an APC application, you can stabilize operations while simultaneously optimizing production or energy usage, leading to a deeper insight into your production processes. This term encompasses a wide array of methods and technologies that complement fundamental process control systems, which are primarily constructed using PID controllers. Some examples of APC technologies include LQR, LQC, H_infinity, neural networks, fuzzy logic, and Model-Based Predictive Control (MPC). An APC application continually optimizes plant operations every minute, round-the-clock, seven days a week, ensuring consistent efficiency. Among these technologies, MPC stands out as the most widely adopted within the industry, as it utilizes a process model to forecast the plant's behavior for the near future, typically ranging from a few minutes to several hours ahead, thus providing a strategic advantage in operational planning. Through the continual refinement of processes, APC not only improves efficiency but also contributes to long-term sustainability goals.
API Access
Has API
No
API Access
Has API
No
Integrations
IBM Maximo Application Suite
No
SAP Cloud Platform
No
Pricing Details
No price information available.
Free Trial
Yes
Free Version
No
Pricing Details
No price information available.
Free Trial
Yes
Free Version
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
Yes
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
No
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
Yes
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
Yes
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
Yes
Live Rep (24/7)
Yes
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
No
In Person
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
Yes
In Person
Yes
Vendor Details
Company Name
Isograph
Country
United Kingdom
Website
www.isograph.com/software/availability-workbench/
Vendor Details
Company Name
Inca Tools
Country
Netherlands
Website
www.incatools.com/advanced-process-control/
Product Features
Simulation
1D Simulation
No
3D Modeling
No
3D Simulation
No
Agent-Based Modeling
No
Continuous Modeling
No
Design Analysis
No
Direct Manipulation
No
Discrete Event Modeling
No
Dynamic Modeling
No
Graphical Modeling
No
Industry Specific Database
No
Monte Carlo Simulation
No
Motion Modeling
No
Presentation Tools
No
Stochastic Modeling
No
Turbulence Modeling
No