Build AI data lakes to optimize data-driven collaboration, safeguard planning and forecasting, and drive supply chain cost efficiencies that protect profits and grow your income
Imagine getting thousands of tables and 300+ different spread sheets. Each tab for each workbook has different data and some of it does not have columns. There are no column headers. You can dump all of this data into a large language model (LLM) and it should figure out what something is. But first you have to train your LLM.
This process is feature extraction and it’s used when deploying AI in manufacturing supply chains.
When manufacturers with extended contract manufacturing supply chains like Dell, General Motors or Samsung contract services like Snowflake, Databricks, Azure Synapse or BigQuery…it’s a multi-million dollar project that can last forever.
This is because ETL data cleansing – which is the process of extracting, transforming and loading (ETL) combined data from multiple sources into a large, central repository called a data warehouse or data lake to ensure manufacturers use only quality and relevant data – can last forever.
Bayesian networks and data processing
ETL data processing is simple but good ETL requires domain expertise (e.g., subject matter experts). Selecting the right people is important and if the right process is in place ETL projects don’t have to last forever.
In most large manufacturing enterprises ETL can be performed in four or five meetings of up to 30 people. It should also be mandated that every person identified to attend these ETL meetings must attend each meeting.
Initially, every person is assigned a workbook with tabs for them to label columns and if a person cannot determine what a column should be labeled there is always someone else in the meeting who can. ETL project management in this manner can save months and months of incorrect labeling.
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AI enhances EMS-OEM electronic manufacturing opportunities
But most large manufacturers have commodity sourcing and supply chain category managers located all over the world and bringing everyone physically together at one location is not suitable. So solving ETL challenges within a project’s timeframe often times requires building a fortified model that can figure out what all of the data is and how it should be labeled. Good artificial intelligence practitioners with the right subject matter experts can build good models with very limited information.
Enter Bayesian networks. Other names include a Bayes network, belief network or decision network. These are probabilistic, graphical models that conduct a Bayesian statistical analysis identifying best practices for a particular industry. In this business case, EMS manufacturing industry and a Bayesian network can be used to help train your model.
Electronics OEM equipment companies executing ETL for their AI supply chain can then see model relevancy progress from 50 per cent, to 60 per cent, to 85 per cent, to 95 per cent… The period of time it takes to get to 95 per cent, and above, is determined based on how much capex budget is allocated to pay for servers. What has taken forever can now be done in hours. Even minutes.
ETL project managers and subject matter experts help keep these AI projects on track by asking the right questions to help build trust in your data lake. Is this supply chain data, and if so, where in the supply chain or, where in the project, do you think this is from? Why?
Managing EMS programs: One-to-many
Today, as enterprise manufacturers have learned Industry 4.0 did not deliver what they wanted, you realize your supply chain remains analog and did not transform to digital manufacturing as you hoped.
Meanwhile, true manufacturing upstream and downstream visibility and collaboration is possible.
A big problem for manufacturing enterprises, whether you are producing printed circuit board (PCB) assemblies or complex, high-mix and large box build system integrations, is manufacturers struggle to effectively manage vast amounts of structured and unstructured data.
This impacts your organization’s operating input costs, workforce efficiency, supply chain effectiveness, income growth capabilities, and more.
A truly digital, smart manufacturing supply chain is your real competitive advantage.
Accurate data labelling and integration of data from all your ERP vendor and supplier sources, combined with machine learning (ML) and AI applied to your manufacturing execution system (MES) can reduce your materials spend and optimize your bill-of-materials, drive down your material scrap and total landed cost, provide clearer spend visibility with product change notices (PCN) and greater capacity planning flexibility, and more.
Program managers tasked with managing EMS providers gain access to advanced analytics and are able to scale EMS manufacturing effectively and accurately across your entire supply chain.
Venture Outsource technology education and training services can help program managers fortify and run better contract manufacturing programs.
We enable program managers to engage and manage a vast number of people outside of your organization in a comprehensive manner – transforming your analog supply chain to digital with more automation and better coordination of people across locations and geographies.
Program managers quickly come up-to-speed on so many variables that influence your EMS program success. You become more effective managing your extended contract EMS provider supply chain.
CFOs and the office of compliance
Comprehensive and accurate manufacturing supply chain data integration also helps create more informed decision-making for your organization in various other ways.
A more effective procurement department combined with, better sales and operations planning (S&OP), work order and production management, better inventory and logistics execution and more effective collaboration within your organization, and across your entire supply chain, generates more value from position of strength.
Additionally, the significance of connecting accurate data to help reduce costly supply chain risks and address potential errors and mistakes made for manufacturers in matters pertaining to country-of-origin (COO), UNSPS code management and HTS codes accuracy plus, tying all of this together with a multitude of contracts and agreements governing your trust in the manufacturing enterprise relationships (rules of engagement) with your supply chain partners cannot be underestimated.
You can also achieve more effective management execution against tariffs, TAA or other import-export supply chain compliance requirements. All of this can help manufacturers avoid costly penalties and customs delays plus, the added benefits to shareholders because your company is less likely to have to restate manufacturing financial statements.
Essentially, your manufacturing operations and supply chain become more efficient, you increase your shipping commits against higher quality and on-time product resulting in more satisfied customers while you increase and protect your hard-earned profits and free up more time to focus on growing your income.
Interested in learning more? Fill in the form on this page to see how Venture Outsource technology services can help you.
