Loading a Keyword and Evaluating the Information
You ask for quite a bit. The webpage is dynamic, so you would need to run an automated browser, navigate to the search page, enter the service number, press "search" and see if there is any item indicating a digital copy.

One way to do this is in Python, a free programming language.
Find Python here and a "howto install" tutorial here.

Make sure you install Python with pip, since it lets you install additional free modules very easily. To install additional packages you simply need to type cmd in the search field in windows. This shows you the command line interface (a black window). When you have Python with pip installed, you can simply type pip install XYZ (press enter), to install the package XYZ (where XYZ is the name of the package).

You also need to download the Selenium Chrome driver (the version must match the version number of you current Chrome browser). This free software allows Python to automatically use Chrome to browser pages. The Chrome driver is a single file, which must be copied to the place where you have Python on your computer. 

The script below does exactly what you want. It searches a list of "numbers" from an excel file one by one on the NAA page. For each request, the script looks for digital documents and "notes" the number of found digital documents. Finally, the results are saved to an excel file. My dummy result would look like:

     servnr  digicopy
0      1234         2
1      6516        15
2     51651         2
3  51651651         0


Maybe you have a friend or someone in your family who can help you install Python. Usually this is a little daunting for people with no programming experiance. If you elaborate my script below, you could even download the digital documents or extract information (e.g. by using OCR software like tesseract).

Basic code for the webcrawler:

# Import required additional packages (to be installed via pip first)
from bs4 import BeautifulSoup 
from urllib.request import urlopen 
import re, time, datetime, json, requests
import pandas as pd
# Chrome Webdriver https://chromedriver.chromium.org/downloads
from selenium import webdriver
from selenium.common.exceptions import TimeoutException
from selenium.webdriver.common.keys import Keys
from selenium.webdriver.common.by import By

# When you see something like "ModuleNotFoundError: No module named 'openpyxl'"
# You need to install the pip package, e.g. pip install openpyxl
# Install pip packages in the console window (type cmd in the search field in Windows bottom left, open it, type pip...)

# Load Excel containing service numbers 
# Change the path to the file is needed
df = pd.read_excel('D:/service_numbers.xlsx')

# Start chrome driver https://chromedriver.chromium.org/downloads
options = webdriver.ChromeOptions()
#options.add_argument('headless') # in background option
options.add_argument('log-level=3')
browser = webdriver.Chrome(chrome_options=options)

# Set up empty data frame to store results
results = pd.DataFrame([])

# Loop over each number (aka row) in the excel file (column name 'snr')
for s in df['snr']:
    browser.get("https://www.naa.gov.au/")
    time.sleep(0.5)
    # Go to record search 
    browser.find_element_by_xpath("//*[@id=\"block-naa-mainpagecontent\"]/div/div[4]/div[2]/div/div/div/div/a").click()
    time.sleep(0.5)

    # Find searchfield and send number "s", press enter
    print("Loading number %s" %s)
    searchfield = browser.find_element_by_xpath("//*[@id=\"ContentPlaceHolderSNR_tbxKeyword\"]") # find field    
    searchfield.send_keys(s) # enter searchterm (the service number)
    searchfield.send_keys('\n') # press enter
    time.sleep(0.5)

    # Load the content of the current page (I do not iterate over all resultrs but only look at the first page here)
    soup = BeautifulSoup(browser.page_source, "html.parser")
    table = soup.find("table", id="ContentPlaceHolderSNR_tblItemDetails")
    # You can also load/print the entire table, you can even go directly to the digital contant (if present)
    #print(table.text)

    # See how many "images" indicating digital content are there
    imgs = soup.find_all('img', {'class':'digital_copy'})
    try:
        numberofdigiitems = len(imgs)
    except:
        numberofdigiitems = 0
    print("There are %s digital copys" %numberofdigiitems)

    # Append result to data frame
    results = results.append(pd.DataFrame({'servnr': s, 'digicopy': numberofdigiitems}, index=[0]), ignore_index=True)

print(results.head())

# Save to excel
results.to_excel("D:/myresults.xlsx", index=False)