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Manufacturing Enterprise Systems (MES) - NSF Grant FAQs

What is the NSF Manufacturing Enterprise Systems (MES) program?

The NSF Manufacturing Enterprise Systems (MES) program is a discretionary research grant opportunity focused on advancing how manufacturing enterprises are designed, planned, and operated. It emphasizes research that strengthens the analytical and computational foundations used to run modern manufacturing and distribution systems, especially when multiple facilities, partners, or supply chain entities work together as an extended enterprise.

What kinds of projects does MES aim to fund?

MES aims to fund research projects that improve decision-making methods for manufacturing and related logistics operations. The program seeks work that advances theory and methods while also showing a clear path toward implementable solutions that could realistically be used in industry or other operational environments.

What is the main research focus of this opportunity?

The main research focus is on decision-making methods that support planning, monitoring, control, scheduling, and coordination across manufacturing and distribution activities. The opportunity highlights methods that help enterprises decide what to produce, when to produce it, how to allocate resources, how to sequence jobs, how to coordinate production with shipping and inventory, and how to respond to changing conditions.

What does NSF mean by an "extended enterprise" in this program?

In the MES context, an extended enterprise refers to manufacturing and distribution operations that span multiple facilities or involve multiple partners across a supply chain. The program is interested in methods that work across interconnected entities rather than isolated single-site operations.

What technical areas are explicitly within scope?

The opportunity explicitly highlights tools and approaches for planning, monitoring, control, and scheduling across manufacturing and distribution. It also emphasizes analytical and computational foundations, including methodological innovation such as models, optimization, simulation, control, scheduling, decision analytics, and computational methods.

Does the program emphasize practical implementation, or primarily theory?

MES emphasizes practicality alongside theory. NSF is looking for research that advances methods and foundational knowledge, but also demonstrates a credible path toward implementable solutions that could realistically be deployed in operational manufacturing environments.

What kinds of manufacturing decisions might a strong MES proposal address?

Examples mentioned in the opportunity include decisions about what to produce and when, how to allocate equipment and labor, how to sequence jobs, how to coordinate production with shipping and inventory, and how to adapt operations when conditions change.

How important are uncertainty and risk in MES proposals?

Uncertainty and risk are a stated priority. The program is explicitly interested in optimizing manufacturing enterprises under significant uncertainty and risk, focusing on real-world variability and disruptions.

What types of uncertainty or variability are specifically referenced?

The opportunity references demand swings, supplier disruptions, machine downtime, quality problems, transportation delays, price volatility, and broader operational risks as examples of uncertainty and variability that proposals may address.

What approaches align with the uncertainty and risk emphasis?

Approaches that quantify uncertainty, incorporate it into planning and control decisions, and produce robust or adaptive policies align well with the program priorities, based on the synopsis.

What is the Funding Opportunity Number for this listing?

The listing is published under Funding Opportunity Number PD 10 1786, titled Manufacturing Enterprise Systems.

What category is this opportunity listed under?

It is categorized under Science and Technology and other Research and Development.

What type of funding instrument is MES in this listing?

The mechanism indicated is a grant.

Is cost sharing or matching required?

No cost sharing or matching requirement is listed in the provided record.

Who is eligible to apply based on the listing?

Eligibility is described as unrestricted, meaning it is open to any type of entity, subject to any additional eligibility clarifications contained in the full program text.

What is the CFDA number associated with this opportunity?

The program is associated with CFDA 47.041 (Engineering Grants).

When was this opportunity posted?

The posted date shown in the record is Aug 20, 2010.

What deadlines are indicated in the listing?

The listing indicates annual deadline windows of September 1 and October 1, and January 15 and February 15, annually.

Is this listing current, or has it been archived?

The listing is archived and is noted as replaced by a later version identified as 12 1786. The archive date shown is Dec 9, 2011.

Why does the record show expected awards and estimated total funding as 0?

The record shows expected awards and estimated total funding as 0, which typically indicates the entry is informational, archived, or that funding levels and award counts are handled through broader NSF program budgets rather than specified in this particular synopsis.

Where should applicants look for complete details beyond this synopsis?

The listing references a program description link for complete details and indicates that any additional eligibility clarifications and full requirements would be contained in the full text.

Who should be contacted for technical issues accessing the announcement?

The listing directs applicants to NSF Grants.gov support for technical issues related to accessing the announcement.

What characteristics are implied to make a proposal competitive?

Based on the provided description, competitive proposals are likely to combine strong methodological innovation with clear relevance to enterprise-scale manufacturing operations and supply chain-connected production systems, and to address complex, high-impact operational problems with implementable approaches, particularly where uncertainty, variability, and risk are central.