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Model Predictive Control Jobs in Ohio (NOW HIRING)

By utilizing the Just-In-Time production model we are able to identify and solve problems ... Perform basic preventive/predictive maintenance. * Participates in improvement activities.

... Modeling Skills * Math optimization and prescriptive analytics * Machine learning and predictive ... Git for version control * n8n and Power Automate * Azure Logic Apps What's in it for you?

... Modeling Skills * Math optimization and prescriptive analytics * Machine learning and predictive ... Git for version control * n8n and Power Automate * Azure Logic Apps What's in it for you?

Millwright

Defiance, OH ยท On-site

$35 - $41.58/hr

Corrective, preventative and predictive maintenance on industrial manufacturing equipment and/or ... Demonstrates role model behavior for safety, integrity and ethical standards. * Ensure all work ...

Head of AI

Columbus, OH ยท On-site

... of predictive maintenance. As we enter the next phase of rapid growth, we are seeking people to ... Partner with executive leadership to define AssetWatch's AI-native vision, operating model, and ...

Software Engineer II

Amherst, OH

$85K - $116K/yr

... predictive maintenance, and operational efficiency. Essential Job Duties and Responsibilities ... Experience implementing, integrating, or deploying AI/ML models or services within software ...

Showing results 41-60

Model Predictive Control information

What is model predictive control?

Model Predictive Control (MPC) is an advanced method of process control that uses a mathematical model to predict and optimize the future behavior of a system. It works by solving an optimization problem at each control step to determine the best sequence of control actions, taking into account system constraints and objectives. MPC is widely used in industries such as chemical processing, energy, and automotive because it can handle multivariable control problems and anticipate future events. Its predictive nature allows for improved performance, stability, and efficiency compared to traditional control methods.

What are the typical challenges faced by engineers working with model predictive control systems in an industrial setting?

Engineers working with Model Predictive Control systems often encounter challenges related to model accuracy, computational demands, and real-time implementation. Ensuring the process model accurately represents the plant dynamics is critical, as discrepancies can lead to suboptimal control performance. Additionally, MPC algorithms can be computationally intensive, particularly for large-scale or fast processes, requiring careful tuning and optimization to maintain real-time operation. Collaboration with process engineers and IT specialists is common, as integrating MPC with existing control systems and plant infrastructure is a key part of the role.

What are the key skills and qualifications needed to thrive as a model predictive control engineer, and why are they important?

To thrive as a Model Predictive Control Engineer, you need strong foundations in control theory, applied mathematics, and process engineering, usually supported by a degree in engineering or a related field. Proficiency with simulation tools such as MATLAB/Simulink, programming languages like Python or C++, and familiarity with industrial automation systems are typically required. Analytical thinking, problem-solving abilities, and effective communication skills help distinguish top performers in this role. These skills are essential for designing, implementing, and optimizing advanced control algorithms that improve system performance and reliability in complex industrial environments.

What is the difference between Model Predictive Control vs Control Systems Engineer?

AspectModel Predictive ControlControl Systems Engineer
CredentialsEngineering degree, control theory, process modelingEngineering degree, control systems, automation
Work EnvironmentIndustrial automation, process control, manufacturingDesign, develop, and maintain control systems across industries
Industry UsageProcess industries, chemical, oil & gas, manufacturingAutomation, robotics, embedded systems, industrial sectors

Model Predictive Control (MPC) focuses on advanced control algorithms for optimizing processes, while Control Systems Engineers design and implement various control systems. MPC is a specialized skill within control engineering, often requiring knowledge of process modeling and optimization, whereas Control Systems Engineers have broader responsibilities across multiple control technologies. Both roles are essential in industrial automation but differ in scope and application.

What does a model predictive control do?

A Model Predictive Control (MPC) engineer designs control systems that use a mathematical model to predict future system behavior and optimize control actions accordingly. MPC is commonly used in industries like process control and robotics, requiring skills in control theory, programming, and system modeling. The role involves developing algorithms, tuning controllers, and ensuring system stability and efficiency.

What job categories do people searching Model Predictive Control jobs in Ohio look for?

The top searched job categories for Model Predictive Control jobs in Ohio are:

What cities in Ohio are hiring for Model Predictive Control jobs?

Cities in Ohio with the most Model Predictive Control job openings:

Infographic showing various Model Predictive Control job openings in Ohio as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution.

Senior Reliability Engineer -- Lewis Center, OH

TWC Global Services LLC

Lewis Center, OH โ€ข On-site

Contractor

Re-posted 27 days ago


Job description

Job Title: Senior Reliability Engineer

Location: Lewis Center, OH (Onsite)

Job Type: Long-term contractual positions – 12+ Months

Responsibilities:

Senior Project Management:

  • Schedule Management - consisting of activity definition and sequencing, resource estimating, duration estimating, schedule development, and schedule control activities.
  • Scope Management - consisting of project initiation, scope planning, scope definition and scope change control activities.
  • Cost Management - consisting of resource planning, cost estimating, budgeting and cost control activities, and appropriate revenue recognition.
  • Risk Management - consisting of risk management planning, risk identification, risk quantitative and qualitative analysis, response planning, monitoring, and control activities.
  • Quality Management - consisting of quality planning, quality assurance and quality control activities.
  • Communications Management - consisting of communications planning, information distribution, progress and performance reporting, and stakeholder.
  • Develops Project Master Plans to define the execution of the project, how the progress will be tracked, monitored and controlled.
  • Client Management - Oversee client interactions and expectations for multiple or large-scale projects. Anticipates client’s needs and proposes alternative business solutions capitalizing upon opportunities to increase customer satisfaction and deepen client relationships.

Reliability Engineering:

  • Lead team efforts in the development of risk-based asset maintenance plans that include, value added preventative maintenance tasks, predictive, condition based and remote monitoring opportunities in order to mitigate reliability risks.
  • Develop, facilitate and lead Reliability training programs for internal and external customers.
  • Develop, Facilitate and lead PPM Training Programs for internal and external Customers, Machine Operators and Maintenance Personnel.
  • Utilize standard Engineering practices to assess equipment operational and reliability risk, using FMEA, Process Flow Diagrams, Value Stream Mapping, Relationship Modeling, Lean Systems analysis and any other engineering tools as may be necessary.
  • Provide technical management and support for the development of the facility’s equipment hierarchy.
  • Provide leadership for statistical methods to analyze asset failure data to determine the need for adjustments in MRO inventory, planned maintenance frequencies, and equipment design.
  • Use statistical methods and reliability modeling to determine optimized equipment maintenance strategies based on cost of process downtime, cost of direct maintenance, MTBF, MTTR, EHS, safety, and other key metrics.
  • Oversee maintenance tasks to mitigate risk of equipment failure.

Qualifications:

  • A bachelor’s degree in Mechanical Engineering or equivalent related experience. Master degree preferred.
  • Minimum of 8 years in a Management capacity as a Reliability Engineer, Manufacturing Engineer, or Maintenance Manager / Engineer working in a discrete manufacturing environment such as Life Sciences, Automotive, Energy, or Consumer Goods.
  • Certified Maintenance and Reliability Professional (CMRP), Certified Reliability Leader (CRL), or Certified Lean/Six Sigma Black Belt preferred.
  • Project Management Professional (PMP) certification a plus.
  • Must have in-depth working knowledge of Risk-Based analysis tools such as Criticality Analysis and Failure Modes Effect Analysis.
  • Experience working with Reliability Centered Maintenance (RCM) and/or Total Productive Maintenance (TPM) programs preferred.
  • Demonstrated experience and understanding of Root Cause Failure Analysis (RCFA).
  • Understanding of Preventive / Predictive Maintenance technologies, strategies, and the ability to lead teams in the development and implementation of sustainable systems.
  • Understanding of Bill of Materials, Critical Spares, and Asset Hierarchy and how each impacts the optimization of asset maintenance systems.
  • Must have thorough knowledge of Technical Drawings /Blue Prints, P&IDs, and technical manuals.
  • Working knowledge of SAP, MAXIMO, MP2, or similar CMMS /EAM software is a plus.
  • Must have a working knowledge of electrical, hydraulic and pneumatic principles and their use on mechanical systems.
  • Must have working knowledge of tool room and assembly processes and practices.
  • Good oral, written, and presentation skills, ability to work with and motivate team members.
  • Experience working with Microsoft Word, Excel, PowerPoint, Access, Visio, and Project.
  • Willingness to take responsibility for key aspects needed for job completion.
  • Hands-on experience in manufacturing, machine debug, and root cause failure analysis.
  • Willing to travel up to 75% (Domestic and International travel is possible.)