Last week, CIO made the case in “How Manufacturers Make the Most of Machine Data” that supply chain professionals should be working more closely with information technology professionals to collect and use the data machines generate.
Disconnects between the factory floor and other departments create “significant lag times for management to access, analyze, and act on data from the manufacturing and development processes,” Michael Nadeau writes for CIO. “Not having this data in real time could create problems with planning, inventory control, the supply chain, or meeting customer expectations.”
CIO reports that new equipment now comes wired for the web, while older equipment can be retrofitted—both enabling machine data to connect directly into companies’ enterprise resources planning (ERP) systems. Some manufacturers still are resisting this connectivity, for “the same old reasons for avoiding any significant technology project: cost, resistance to change, and lack of understanding of the [return on investment].”
One expert interviewed by CIO, Magnus Wilkerson, a professor of production systems at Sweden’s Matardalen University, explains that industrial digitization has two benefits. First, it integrates data throughout the value chain to improve operational processes, including supply chain. Second, machine data can be critical to products and their development by enabling virtual production of new products and processes.
Wilkerson describes four key challenges for any company implementing machine data:
- The new technology shouldn’t add new layers of management hierarchy. Instead, it should enhance existing continuous improvement.
- Revamping existing systems can be cumbersome, especially when there are numerous platforms. Upgrades should come in stages. “It is necessary to use these windows of opportunity in a conscious development towards a smart factory vision,” Nadeau writes.
- Do not jeopardize the quality or delivery of the machine by adding complicated technologies susceptible to failure.
- Use the new technologies to test current processes and pre-engineering platforms, thus, speeding up adoption and best practices.
Using data for business decisions
Consider how big data is evolving, and the Internet of Things (IOT) is expanding. IOT is defined in the APICS Dictionary, 15th edition, as follows: “An environment in which objects, animals, or people are provided with unique identifiers and the ability to transfer data over a network without requiring human-to-human or human-to-computer interaction. This allows objects to be sensed and controlled remotely across existing network infrastructure, creating opportunities for more direct integration between the physical world and computer-based systems.”
At APICS, we hope to keep supply chain professionals informed about best practices in the field and emerging trends. Through a variety of articles, conference presentations, and research, we have been reporting about big data and the IOT. For example, “Exploring the Big Data Revolution,” is an APICS research report that describes the opportunities and advantages big data presents.
According to the report, “professionals who use big data effectively seek to improve forecasting, planning, situational awareness, and information by creating a comprehensive understanding of complex perspectives. Big data helps to create a fluid perspective—from high-level strategic views to tactical views—by showing the connections, relationships, dependencies and patterns that previously were too difficult to interpret.”
To view this report, visit www.apics.org/sites/apics-supply-chain-council/research-and-publications/publications/apics-big-data. Find out more about APICS research at www.apics.org/sites/apics-supply-chain-council/research-and-publications/publications.