Conceptual Design
From designing a new process to an enterprise-wide information system and automation roadmap -whatever your need is, our expertise helps.
When you are setting up a new plant, upgrading an existing one, or undertaking digitization, your success depends largely on the choices made in the beginning.
This is where Conceptual Design comes in.
Sound Conceptual Design helps you make decisions that ensure long-term economics, efficiency, scalability, and safe operations. We combine chemical engineering fundamentals, operating experience, and practical business understanding to design solutions.
The objective is to create a workable design and to help you choose the most effective path forward.
New Process Conceptualization
You know that scaling up chemical processes is a major challenge.
We start with your laboratory results, pilot plant data, or an early-stage idea, and design a new industrially feasible processing scheme. The scheme covers
- PFDs and P&IDs
- Material flows
- Utility requirements
- Equipment choices
- Operating philosophy
- Scaling-up considerations
We assess technical feasibility as well as commercial practicality, helping you move confidently from experimentation to production planning.
We develop preliminary mass and energy balances to validate the process concept and identify potential bottlenecks early. Reaction kinetics, phase equilibria, and separation requirements are examined to determine whether the chemistry will behave at scale as it does in the lab.
The result is a solid platform for all engineering and financial decisions.
Control Scheme Design
Your process control system is the brain of your plant. Once the right equipment capacities are built, process performance depends on the control system.
Architecture of control system: The architecture decides how stable your operations will be. A capable control system ensures quality consistency, safety, and optimal operator effort.
Instrumentation philosophy: Decisions about direct or indirect measurements, feedback loop configurations, criteria for event triggers, and data processing are at the core of every control scheme.
- All the above aspects must be thought through right from the start of your project. Our Control Scheme Design ensures this.
- We determine areas in which your process is inherently sensitive — which variables can drift, which disturbances can propagate quickly, and where operator response time can be crucial.
- Control loop configurations like single-loop PID, cascade, feedforward, or ratio control are selected based on process dynamics.
- We also define interlock logic and alarm criteria at the conceptual stage, so that safety aspects are incorporated right at the design stage, and not as an afterthought.
We design control schemes that handle process dynamics and meet production objectives.
Our control philosophy document gives your automation vendor and your engineering team a clear, unambiguous brief to work from.
Data Management Architecture
Advances in AI\ML technologies have placed powerful tools at everyone’s fingertips. But to use them, you need a deep understanding of the data that your plant is generating or will generate. You also need to use data to achieve your goals. We provide you with this expertise.
From history to prediction
You need a new approach to data that shifts focus from history to prediction -from reports to early warnings, from trial and error to intelligently conceived trials.
- We undertake a data audit. We analyze tag lists, historian configurations, LIMS outputs, batch records, and manual logs, each having different structures and different levels of trustworthiness. We identify areas that need upgrading, measurement precision, or frequency.
- We architect plant-wide or enterprise-wide data management systems that connect operations, quality, maintenance, planning, and management functions.
- We define how data flows from field instruments, how it is connected to various process steps, and how it is presented to operators, process engineers, reliability teams, and plant management.
The Data Management Architecture is a blueprint of your information system requirements.